[{"collection_id":"af893e86-8e9f-41f1-a474-ef05359b1fb7","collection_url":"https://cellxgene.cziscience.com/collections/af893e86-8e9f-41f1-a474-ef05359b1fb7","collection_version_id":"c1b538fd-0f01-41c8-a504-6f44626916c2","consortia":["CZI Cell Science"],"contact_email":"ruichen@bcm.edu","contact_name":"Rui Chen","created_at":"2026-06-09T23:02:06+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ed419b4e-db9b-40f1-8593-68fdf8dfb076","dataset_version_id":"c8da6eeb-84d7-4379-a332-1bf6107859d6","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"aad97cb5-f375-45ef-ae9d-178e7f5d5180","dataset_version_id":"9db639c3-5c9c-4b8f-b285-25ed5d335417","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"8f10185b-e0b3-46a5-8706-7f1799225d79","dataset_version_id":"45e411d4-c103-4c28-84a9-cb5320f873ba","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"359f7af4-87d4-4117-9d6c-ca4cfa1f3f0b","dataset_version_id":"e3c7aa91-5edd-416e-965e-17bef75462d4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"11ef37ee-2173-458e-aab8-7fe35da8e47b","dataset_version_id":"5903aa1b-c323-4ae0-abfc-8100e2eba799","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0129dbd9-a7d3-4f6b-96b9-1da155a93748","dataset_version_id":"7f2413c4-38c2-4559-a959-e649e2118586","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"00e5dedd-b9b7-43be-8c28-b0e5c6414a62","dataset_version_id":"3d0dcefd-cdf2-4b12-89df-c871e9a3c4b8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"macula lutea proper","ontology_term_id":"UBERON:0002822","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]}],"description":"The retina is the innermost tissue of the eyes of human and most other vertebrates. It receives the information of the visual images like the film of a camera and then translates the images into neural signals. As the neural signals get transduced to and processed by the brain, the visual perception is created. Different cell types in the retina functions in various ways to accomplish the whole procedure.\n\nIn the human retina, the major cell types could be further classified into subtypes based on their morphology, physiology features or functions, and molecular markers. To date, it is estimated that there are over 70 cell types in the human retina according to a previous primate study. Reliable classification of those neurons is required to manage the complexity of such level. Single-nuclei RNA-seq were carried out to profile well-characterized healthy human retina from six individual donors using the 10x Genomics technologies. Each donor retina was dissected into three geographic regions: the fovea, macula, and peripheral retina and flash frozen afterwards. A fractionation protocol was developed to enrich nuclei from rare neuron cell types, including bipolar cells, amacrine cells, and retinal ganglion cells. In total, over 60 cell types are identified in our dataset, making the currently most comprehensive single-cell profiling of adult human retina.","doi":"10.1016/j.xgen.2023.100298","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://retina-atac.cells.ucsc.edu/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/9c20a245-f2c0-43ae-82c9-2232ec6b594f"},{"link_name":"GSE226108","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE226108"}],"name":"Single-cell transcriptomic atlas for adult human retina","published_at":"2021-10-29T22:14:24+00:00","publisher_metadata":{"authors":[{"family":"Liang","given":"Qingnan"},{"family":"Cheng","given":"Xuesen"},{"family":"Wang","given":"Jun"},{"family":"Owen","given":"Leah"},{"family":"Shakoor","given":"Akbar"},{"family":"Lillvis","given":"John L."},{"family":"Zhang","given":"Charles"},{"family":"Farkas","given":"Michael"},{"family":"Kim","given":"Ivana K."},{"family":"Li","given":"Yumei"},{"family":"DeAngelis","given":"Margaret"},{"family":"Chen","given":"Rui"}],"is_preprint":false,"journal":"Cell Genomics","published_at":1685577600.0,"published_day":1,"published_month":6,"published_year":2023},"revised_at":"2026-06-11T16:52:24+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3a5dbf8a-9b3e-4309-b4c5-d8a024f83734","collection_url":"https://cellxgene.cziscience.com/collections/3a5dbf8a-9b3e-4309-b4c5-d8a024f83734","collection_version_id":"c656236c-fc37-4470-aef1-799af222a821","consortia":["LungMAP"],"contact_email":"xinsun@ucsd.edu","contact_name":"Xin Sun","created_at":"2026-06-10T03:39:38+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d68a8b48-abf0-4bd5-8834-155d34ec448a","dataset_version_id":"83bbeaaf-f5e0-42ac-be8a-dbc4e0c0d433","disease":[{"label":"bronchopulmonary dysplasia","ontology_term_id":"MONDO:0019091"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"middle lobe of right lung","ontology_term_id":"UBERON:0002174","tissue_type":"tissue"}]}],"description":"Bronchopulmonary dysplasia (BPD) is a chronic lung disease characterized by alveolar dysplasia in newborns that are typically born prematurely. In this study, single-nucleus RNA-Sequencing was performed on BDPD infants (n=15) and age matched controls (n=8) who died from complications associated with BPD (4 months to 3 years of age).","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://data-browser.lungmap.net/projects/1977dc47-8414-4263-a870-6b0f207d8ab3"}],"name":"Bronchopulmonary Dysplasia","published_at":"2025-02-03T17:14:54+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:53:15+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"16876983-d454-43db-a8ec-77fafca9bf38","collection_url":"https://cellxgene.cziscience.com/collections/16876983-d454-43db-a8ec-77fafca9bf38","collection_version_id":"ea4e5a38-8adb-4ca3-94e0-3cb07c661091","consortia":[],"contact_email":"ryan.corces@gladstone.ucsf.edu","contact_name":"Ryan Corces","created_at":"2026-06-10T02:12:51+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"e88a8e7c-0586-4690-8aa6-34efd7076f7a","dataset_version_id":"02e1d36f-3019-49c9-aa3d-3a7df7ae9fd8","disease":[{"label":"Parkinson disease","ontology_term_id":"MONDO:0005180"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"cingulate gyrus","ontology_term_id":"UBERON:0002967","tissue_type":"tissue"},{"label":"middle temporal gyrus","ontology_term_id":"UBERON:0002771","tissue_type":"tissue"},{"label":"putamen","ontology_term_id":"UBERON:0001874","tissue_type":"tissue"},{"label":"substantia nigra","ontology_term_id":"UBERON:0002038","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"5fa72b3e-999e-4560-a105-391d109574da","dataset_version_id":"5451683b-f184-4bd5-8fb1-401bf1a467c6","disease":[{"label":"Parkinson disease","ontology_term_id":"MONDO:0005180"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"cingulate gyrus","ontology_term_id":"UBERON:0002967","tissue_type":"tissue"},{"label":"middle temporal gyrus","ontology_term_id":"UBERON:0002771","tissue_type":"tissue"},{"label":"putamen","ontology_term_id":"UBERON:0001874","tissue_type":"tissue"},{"label":"substantia nigra","ontology_term_id":"UBERON:0002038","tissue_type":"tissue"}]}],"description":"Complex diseases, by definition, are driven by a large number of genetic variants, many of which reside within the noncoding genome. While genome-wide association studies have identified disease-associated loci, the common variants that they nominate almost universally have low effect sizes and thus the underlying disease associations often only explain a small fraction of the total disease heritability. Unlike common variants, rare variants often have higher effect sizes and cumulatively account for a larger proportion of disease heritability. However, rare variants, and in particular rare noncoding variants, have remained largely under-characterized due to the challenge of predicting variant effects at the scale of ~10,000 variants per individual. Here, we generate a massive-scale multi-omic atlas of gene expression and chromatin accessibility in the human brain and use a multi-pronged functional genomics approach to nominate disease-relevant rare noncoding variants in Parkinson\u2019s disease. Leveraging data from >3.3 million nuclei sampled from 5 brain regions across a cohort of 101 individuals with matched 30x short-read whole genome sequencing, we identify cell type-specific features of PD, call cell type-specific chromatin accessibility and expression quantitative trait loci, map enhancer-gene interactions using cell-type specific chromatin contacts, and train machine learning models to predict the effects of variants on transcription factor binding and gene regulation. We find specific genes to be enriched for functional rare noncoding variants and suggestive of disease association, implicating these genes as risk and protective factors for PD and potential therapeutic targets. Our results highlight the importance of rare noncoding variants in complex disease and provide a roadmap for the application of similar approaches in other disease systems.","doi":"10.64898/2026.03.05.709922","is_pre_analysis":false,"links":[],"name":"Multi-Region Brain Single-Cell Atlas of Parkinson's Disease and Control Samples","published_at":"2026-04-30T17:25:28+00:00","publisher_metadata":{"authors":[{"family":"Menon","given":"Shreya"},{"family":"Turner","given":"Adam W."},{"family":"Chang","given":"Serena H."},{"family":"Johnson","given":"Alia W."},{"family":"Chang","given":"Heather H."},{"family":"Shah","given":"Aayushi J."},{"family":"Zeng","given":"Youjie"},{"family":"Strohlein","given":"Colleen E."},{"family":"Kampman","given":"Lucas"},{"family":"Colston","given":"Courtney"},{"family":"Kozlenkov","given":"Alexey"},{"family":"Dracheva","given":"Stella"},{"family":"Avenali","given":"Micol"},{"family":"Palermo","given":"Giovanni"},{"family":"Ceravolo","given":"Roberto"},{"family":"Valente","given":"Enza Maria"},{"family":"Gabbert","given":"Carolin"},{"family":"Trinh","given":"Joanne"},{"family":"Serrano","given":"Geidy E."},{"family":"Beach","given":"Thomas G."},{"name":"Global Parkinson\u2019s Genetic Program (GP2)"},{"family":"Shulman","given":"Joshua M."},{"family":"Blauwendraat","given":"Cornelis"},{"family":"Montine","given":"Thomas J."},{"family":"Fang","given":"Zih-Hua"},{"family":"Belloy","given":"Michael E."},{"family":"Corces","given":"M. Ryan"}],"is_preprint":true,"journal":"bioRxiv","published_at":1772668800.0,"published_day":5,"published_month":3,"published_year":2026},"revised_at":"2026-06-11T16:53:15+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ad10cef8-9c6c-488f-9b50-d252d49b6837","collection_url":"https://cellxgene.cziscience.com/collections/ad10cef8-9c6c-488f-9b50-d252d49b6837","collection_version_id":"6f05ce2a-2fca-424c-82b7-0226386e1951","consortia":[],"contact_email":"jiyeon.choi2@nih.gov","contact_name":"Jiyeon Choi","created_at":"2026-06-10T02:39:24+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"92594117-6e7c-47bd-bd6b-65c52cea167b","dataset_version_id":"a1e971da-5c35-46fd-acc3-b742735ec7d9","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.","doi":"10.1038/s41467-024-52356-9","is_pre_analysis":false,"links":[{"link_name":"GSE241468","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE241468"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/pumclyy/HLISCA"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/13306592"}],"name":"Context-aware single-cell multiomics approach identifies cell-type specific lung cancer susceptibility genes","published_at":"2026-01-07T20:01:55+00:00","publisher_metadata":{"authors":[{"family":"Long","given":"Erping"},{"family":"Yin","given":"Jinhu"},{"family":"Shin","given":"Ju Hye"},{"family":"Li","given":"Yuyan"},{"family":"Li","given":"Bolun"},{"family":"Kane","given":"Alexander"},{"family":"Patel","given":"Harsh"},{"family":"Sun","given":"Xinti"},{"family":"Wang","given":"Cong"},{"family":"Luong","given":"Thong"},{"family":"Xia","given":"Jun"},{"family":"Han","given":"Younghun"},{"family":"Byun","given":"Jinyoung"},{"family":"Zhang","given":"Tongwu"},{"family":"Zhao","given":"Wei"},{"family":"Landi","given":"Maria Teresa"},{"family":"Rothman","given":"Nathaniel"},{"family":"Lan","given":"Qing"},{"family":"Chang","given":"Yoon Soo"},{"family":"Yu","given":"Fulong"},{"family":"Amos","given":"Christopher I."},{"family":"Shi","given":"Jianxin"},{"family":"Lee","given":"Jin Gu"},{"family":"Kim","given":"Eun Young"},{"family":"Choi","given":"Jiyeon"}],"is_preprint":false,"journal":"Nat Commun","published_at":1726099200.0,"published_day":12,"published_month":9,"published_year":2024},"revised_at":"2026-06-11T16:53:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bd552f76-1f1b-43a3-b9ee-0aace57e90d6","collection_url":"https://cellxgene.cziscience.com/collections/bd552f76-1f1b-43a3-b9ee-0aace57e90d6","collection_version_id":"e96b8037-35f3-40e4-983c-dfe814e7202e","consortia":[],"contact_email":"senbai.kang@chuv.ch","contact_name":"Senbai Kang","created_at":"2026-08-17T22:15:05+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x Next GEM Flex v1","ontology_term_id":"EFO:0920087"}],"dataset_id":"fbdd8c17-b34a-4cbc-abc4-1aeaa294a538","dataset_version_id":"5466ce85-7f19-49e2-9a1b-54646bb84708","disease":[{"label":"invasive ductal breast carcinoma","ontology_term_id":"MONDO:0004953"},{"label":"invasive lobular breast carcinoma","ontology_term_id":"MONDO:0005051"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"parenchyma of mammary gland","ontology_term_id":"UBERON:0036245","tissue_type":"tissue"}]},{"assay":[{"label":"10x Next GEM Flex v1","ontology_term_id":"EFO:0920087"}],"dataset_id":"a77176ec-96c8-4448-a3e7-b56940bdfab6","dataset_version_id":"e9b97c4b-5000-488d-b2e4-505bfb327671","disease":[{"label":"diffuse large B-cell lymphoma","ontology_term_id":"MONDO:0018905"},{"label":"primary cutaneous diffuse large B-cell lymphoma, Leg type","ontology_term_id":"MONDO:0006383"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"arm skin","ontology_term_id":"UBERON:0002427","tissue_type":"tissue"},{"label":"bronchus","ontology_term_id":"UBERON:0002185","tissue_type":"tissue"},{"label":"cervical lymph node","ontology_term_id":"UBERON:0002429","tissue_type":"tissue"},{"label":"duodenum","ontology_term_id":"UBERON:0002114","tissue_type":"tissue"},{"label":"external iliac lymph node","ontology_term_id":"UBERON:0015880","tissue_type":"tissue"},{"label":"stomach","ontology_term_id":"UBERON:0000945","tissue_type":"tissue"}]},{"assay":[{"label":"10x Next GEM Flex v1","ontology_term_id":"EFO:0920087"}],"dataset_id":"1e4214ce-7347-4ec7-97b3-fcf7c1938e8b","dataset_version_id":"4ca422ae-e4ad-4884-9073-7c3799cd9143","disease":[{"label":"lung adenocarcinoma","ontology_term_id":"MONDO:0005061"},{"label":"squamous cell lung carcinoma","ontology_term_id":"MONDO:0005097"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung parenchyma","ontology_term_id":"UBERON:0008946","tissue_type":"tissue"}]}],"description":"Background: \nSeveral technologies can characterise spatial heterogeneity of gene expression in tissues. Their relative strengths and weaknesses have been poorly explored. We compared the output of GeoMx DSP (Nanostring) and Visium CytAssist (10X) full transcriptomes in the analysis of human cancers.\n\no Methods: \nConsecutive sections of archival FFPE blocks (median age 57 months (22-103); median DV200 53.75% (7.2-80.3)) of breast and lung carcinomas (BC/LC; n=4 each) and diffuse large B-cell lymphomas (DLBCL, n=6) were profiled with both platforms, in duplicate for one BC and one LC. GeoMx regions of interest (ROIs) were segmented for tumor (CK/CD20+), CD3+, CD68+ and marker-negative areas of illumination (AOIs). Visium capture spots were annotated for majority cell type based on H&E. Sections were aligned to match Visium spots with GeoMx AOI covering >70% of their areas. \n\no Results:\nBetween 68-84% AOIs (GeoMx) and 89-100% spots (Visium) passed QC, resulting in 376 GeoMx and 36776 Visium data points. Both methods showed high replicate reproducibility, with strong patient effect. Transcriptomes deconvolution showed a mixture of cell types, enriched in the selected AOI type (GeoMx), and according to pathologists\u2019 annotations (Visium). Matching spots/AOIs analysis (598 spots/67 AOIs) showed similar results for capturing cell type mixtures in GeoMx and Visium, with higher variety in stromal compartment for Visium. Independent Differential Expression analysis between biological compartments demonstrated a similar signal in GeoMx and Visium, with higher significance in Visium. \n\no Conclusions:\nWe generated good quality spatial transcriptomics data with GeoMx DSP and Visium CytAssist. Both GeoMx AOIs and Visium spots capture a mixture of cell types, enriched in the expected cell signature. GeoMx enables profiling of expertly selected cell types in predefined tissue areas. 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Single nucleus RNA-sequencing and whole genome sequencing were collected from non-pathological tissue in 75 patients undergoing surgeries for tumor removal or intractable epilepsy. Nuclei were mapped to a publicly-accessible taxonomy of 127 robust cell types identified in middle temporal gyrus (see links) that was used as a reference for mapping cells in Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) to allow cross-study comparisons.  Highly variable cell type abundances and gene expression signatures across donors, particularly in deep layer glutamatergic neurons, are largely unexplained by demographic factors.  We provide this tool to allow exploration of intra- and inter-donor variability and encourage other scientists to expand upon our findings.  Data available from this study web site do not require any additional Institutional Review Board (IRB) approval or permissions.  Patch-seq data is available from adjacent tissue sections from a subset of these donors (see links).","doi":"10.1126/science.adf2359","is_pre_analysis":false,"links":[{"link_name":"Allen Brain Map","link_type":"OTHER","link_url":"https://knowledge.brain-map.org/data/Z4KJ7FC4QZWPP8TV4OK/summary"},{"link_name":"Reference middle temporal gyrus taxonomy","link_type":"DATA_SOURCE","link_url":"https://portal.brain-map.org/atlases-and-data/rnaseq/human-mtg-10x_sea-ad"},{"link_name":"Allen Brain Map Patch-seq","link_type":"DATA_SOURCE","link_url":"https://portal.brain-map.org/explore/classes/multimodal-characterization"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-p3eei0g"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/AllenInstitute/human_variation"}],"name":"HVS: Human variation study","published_at":"2024-08-05T16:51:26+00:00","publisher_metadata":{"authors":[{"family":"Johansen","given":"Nelson"},{"family":"Somasundaram","given":"Saroja"},{"family":"Travaglini","given":"Kyle J."},{"family":"Yanny","given":"Anna Marie"},{"family":"Shumyatcher","given":"Maya"},{"family":"Casper","given":"Tamara"},{"family":"Cobbs","given":"Charles"},{"family":"Dee","given":"Nick"},{"family":"Ellenbogen","given":"Richard"},{"family":"Ferreira","given":"Manuel"},{"family":"Goldy","given":"Jeff"},{"family":"Guzman","given":"Junitta"},{"family":"Gwinn","given":"Ryder"},{"family":"Hirschstein","given":"Daniel"},{"family":"Jorstad","given":"Nikolas L."},{"family":"Keene","given":"C. 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Smith","created_at":"2026-06-10T12:35:53+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"82f6af6d-5313-439a-9936-5e844be49a70","dataset_version_id":"182945c8-d6e7-4e49-b5f8-2c61d68bca14","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"parietal lobe","ontology_term_id":"UBERON:0001872","tissue_type":"tissue"},{"label":"prefrontal cortex","ontology_term_id":"UBERON:0000451","tissue_type":"tissue"},{"label":"primary visual cortex","ontology_term_id":"UBERON:0002436","tissue_type":"tissue"},{"label":"temporal lobe","ontology_term_id":"UBERON:0001871","tissue_type":"tissue"}]},{"assay":[{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"39ed7d98-676d-4b8d-9d0a-0f3b60914ead","dataset_version_id":"91431488-6bc7-46b6-8d64-2c4a3ed8194d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"anterior cingulate cortex","ontology_term_id":"UBERON:0009835","tissue_type":"tissue"},{"label":"caudal ganglionic eminence","ontology_term_id":"UBERON:0004026","tissue_type":"tissue"},{"label":"hippocampal formation","ontology_term_id":"UBERON:0002421","tissue_type":"tissue"},{"label":"medial ganglionic eminence","ontology_term_id":"UBERON:0004024","tissue_type":"tissue"},{"label":"orbitofrontal cortex","ontology_term_id":"UBERON:0004167","tissue_type":"tissue"},{"label":"parietal lobe","ontology_term_id":"UBERON:0001872","tissue_type":"tissue"},{"label":"primary visual cortex","ontology_term_id":"UBERON:0002436","tissue_type":"tissue"}]}],"description":"Osmotic equilibrium and membrane potential in animal cells depend on concentration gradients of sodium (Na+) and potassium (K+) ions across the plasma membrane, a function catalyzed by the Na+,K+-ATPase \u03b1-subunit. Here, we describe ATP1A3 variants encoding dysfunctional \u03b13-subunits in children affected by polymicrogyria, a developmental malformation of the cerebral cortex characterized by abnormal folding and laminar organization. To gain cell-biological insights into the spatiotemporal dynamics of prenatal ATP1A3 expression, we built an ATP1A3 transcriptional atlas of fetal cortical development using mRNA in situ hybridization and transcriptomic profiling of \u223c125,000 individual cells with single-cell RNA sequencing (Drop-seq) from 11 areas of the midgestational human neocortex. We found that fetal expression of ATP1A3 is most abundant to a subset of excitatory neurons carrying transcriptional signatures of the developing subplate, yet also maintains expression in nonneuronal cell populations. Moving forward a year in human development, we profiled \u223c52,000 nuclei from four areas of an infant neocortex and show that ATP1A3 expression persists throughout early postnatal development, most predominantly in inhibitory neurons, including parvalbumin interneurons in the frontal cortex. Finally, we discovered the heteromeric Na+,K+-ATPase pump complex may form nonredundant cell-type\u2013specific \u03b1-\u03b2 isoform combinations, including \u03b13-\u03b21 in excitatory neurons and \u03b13-\u03b22 in inhibitory neurons. Together, the developmental malformation phenotype of affected individuals and single-cell ATP1A3 expression patterns point to a key role for \u03b13 in human cortex development, as well as a cell-type basis for pre- and postnatal ATP1A3-associated diseases.","doi":"10.1073/pnas.2023333118","is_pre_analysis":false,"links":[{"link_name":"phs001272","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001272"}],"name":"Early role for a Na+,K+-ATPase (ATP1A3) in brain development","published_at":"2022-06-03T20:04:07+00:00","publisher_metadata":{"authors":[{"family":"Smith","given":"Richard S."},{"family":"Florio","given":"Marta"},{"family":"Akula","given":"Shyam K."},{"family":"Neil","given":"Jennifer E."},{"family":"Wang","given":"Yidi"},{"family":"Hill","given":"R. 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Single-cell RNA sequencing was performed to profile transcriptomic states of T cells across distinct tissue environments. Protein-derived signals from CITE-seq antibodies are provided as log10-transformed values at the cell level in adata.obs. The raw antibody-derived tag (ADT) count matrix is not included in this dataset.","doi":"10.1038/s41467-026-70751-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://humandbs.dbcls.jp/en/hum0522-v1"},{"link_name":"Github","link_type":"LAB_WEBSITE","link_url":"https://github.com/yyoshiaki/2026_ICI_Nose_et_al"}],"name":"T cells from gastric cancer patients","published_at":"2026-04-09T17:02:44+00:00","publisher_metadata":{"authors":[{"family":"Nose","given":"Yohei"},{"family":"Yasumizu","given":"Yoshiaki"},{"family":"Saito","given":"Takuro"},{"family":"Nakamura","given":"Yamami"},{"family":"Jinushi","given":"Koichi"},{"family":"Fujikawa","given":"Kaoru"},{"family":"Momose","given":"Kota"},{"family":"Yamashita","given":"Kotaro"},{"family":"Tanaka","given":"Koji"},{"family":"Yamamoto","given":"Kazuyoshi"},{"family":"Makino","given":"Tomoki"},{"family":"Takahashi","given":"Tsuyoshi"},{"family":"Ueyama","given":"Azumi"},{"family":"Kurokawa","given":"Yukinori"},{"family":"Sato","given":"Eiichi"},{"family":"Ohkura","given":"Naganari"},{"family":"Sakaguchi","given":"Shimon"},{"family":"Wada","given":"Hisashi"},{"family":"Eguchi","given":"Hidetoshi"},{"family":"Doki","given":"Yuichiro"}],"is_preprint":false,"journal":"Nat Commun","published_at":1775606400.0,"published_day":8,"published_month":4,"published_year":2026},"revised_at":"2026-06-11T16:55:49+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9b02383a-9358-4f0f-9795-a891ec523bcc","collection_url":"https://cellxgene.cziscience.com/collections/9b02383a-9358-4f0f-9795-a891ec523bcc","collection_version_id":"0bb91d14-4427-4e5a-9499-72cd8fead633","consortia":["CZI Cell Science"],"contact_email":"parkerw@wustl.edu","contact_name":"Parker C. Wilson","created_at":"2026-06-10T23:41:25+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"9df60c57-fdf3-4e93-828e-fe9303f20438","dataset_version_id":"6dbfae45-1638-4842-8e84-462acc8366a1","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"}]},{"assay":[{"label":"10x scATAC-seq","ontology_term_id":"EFO:0030007"}],"dataset_id":"13a027de-ea3e-432b-9a5e-6bc7048498fc","dataset_version_id":"01a8c684-c327-47a2-ba8c-adb0892c4c76","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"}]}],"description":"In this study, single nucleus ATAC (snATAC-seq) and RNA (snRNA-seq) sequencing was performed to generate paired (5 donors), cell-type-specific chromatin accessibility and transcriptional profiles of the adult human kidney. The integration of single cell transcriptome and chromatin accessibility datasets enables a deeper understanding of cell heterogeneity.","doi":"10.1038/s41467-021-22368-w","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://genome.ucsc.edu/s/parkercwilson/control_celltype_cr"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=human-kidney-atac"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/2af52a13-65cb-4973-b513-39be38f2df3f"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/p4rkerw/Muto_Wilson_NComm_2020"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://humphreyslab.com/SingleCell/"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/nuclei-isolation-from-human-kidney-for-single-nucl-nahdab6"},{"link_name":"GSE151302","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151302"}],"name":"Single cell transcriptional and chromatin accessibility profiling redefine cellular heterogeneity in the adult human kidney","published_at":"2021-02-25T19:02:14+00:00","publisher_metadata":{"authors":[{"family":"Muto","given":"Yoshiharu"},{"family":"Wilson","given":"Parker C."},{"family":"Ledru","given":"Nicolas"},{"family":"Wu","given":"Haojia"},{"family":"Dimke","given":"Henrik"},{"family":"Waikar","given":"Sushrut S."},{"family":"Humphreys","given":"Benjamin D."}],"is_preprint":false,"journal":"Nat Commun","published_at":1638316800.0,"published_day":1,"published_month":12,"published_year":2021},"revised_at":"2026-06-11T16:55:59+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"8a05eaf6-5680-41f2-9be7-eddc383b178a","collection_url":"https://cellxgene.cziscience.com/collections/8a05eaf6-5680-41f2-9be7-eddc383b178a","collection_version_id":"633a21eb-5a97-401d-9b22-f5fe7181d226","consortia":[],"contact_email":"EichholJ@mskcc.org","contact_name":"Jordan Eicholz","created_at":"2026-06-10T22:40:35+00:00","curator_name":"James 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via gene amplification, mutation, and/or protein overexpression. In a cohort of 42,415 prospectively analyzed solid tumors, 14.5% of urothelial cancers (n=295/2,035) had oncogenic or likely oncogenic ERBB2 alterations (6.7% ERBB2 mutation, 6.3% amplification of wildtype ERBB2, and 1.5% concurrent mutation and amplification). Discordance of ERBB2 mutational status between primary and metastatic disease sites was common in patients with urothelial cancer as was discordance of ERBB2 mutational status between patient-derived organoid/xenograft models and the tumors from which they were derived. In patient-derived urothelial cancer models, the HER2-targeted antibody-drug conjugate (ADC) trastuzumab deruxtecan was significantly more effective than the HER kinase inhibitor neratinib. In a real-world cohort of patients with urothelial cancer treated with trastuzumab deruxtecan, co-mutation and amplification of ERBB2 was associated with exceptional clinical response. Our data support expanded clinical trials of HER2-targeted ADCs for urothelial cancers with low HER2 expression, the clinical testing of HER2 ADCs with alternative cytotoxic payloads, and the development of functional precision oncology platforms capable of assessing payload sensitivity pre-treatment as a guide to individualized therapy selection.","doi":"10.1038/s41467-025-67643-2","is_pre_analysis":false,"links":[],"name":"Determinants of Sensitivity to HER2-targeted Antibody Drug Conjugates in Urothelial Cancer","published_at":"2026-02-12T20:08:38+00:00","publisher_metadata":{"authors":[{"family":"Chen","given":"Ziyu"},{"family":"Tang","given":"Xinran"},{"family":"Eichholz","given":"Jordan E."},{"family":"Mcpherson","given":"Andrew"},{"family":"Thomas","given":"Jasmine"},{"family":"Nagar","given":"Karan"},{"family":"Rustgi","given":"Naryan"},{"family":"Christin","given":"John 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Here, we examined the relationship between immune processes in the respiratory tract and circulation through longitudinal phenotypic, transcriptomic, and cytokine profiling of paired airway and blood samples from patients with severe COVID-19 relative to heathy controls. In COVID-19 airways, T cells exhibited activated, tissue-resident, and protective profiles; higher T cell frequencies correlated with survival and younger age. Myeloid cells in COVID-19 airways featured hyperinflammatory signatures, and higher frequencies of these cells correlated with mortality and older age. In COVID-19 blood, aberrant CD163+ monocytes predominated over conventional monocytes, and were found in corresponding airway samples and in damaged alveoli. High levels of myeloid chemoattractants in airways suggest recruitment of these cells through a CCL2-CCR2 chemokine axis. Our findings provide insights into immune processes driving COVID-19 lung pathology with therapeutic implications for targeting inflammation in the respiratory tract.","doi":"10.1016/j.immuni.2021.03.005","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://data.mendeley.com/datasets/fm7v43jrbk/2"},{"link_name":"","link_type":"OTHER","link_url":"http://www.github.com/simslab/cluster_diffex2018"},{"link_name":"","link_type":"OTHER","link_url":"https://www.covid19cellatlas.org/index.patient.html"}],"name":"Longitudinal profiling of respiratory and systemic immune responses reveals myeloid cell-driven lung inflammation in severe COVID-19","published_at":"2022-03-25T14:56:51+00:00","publisher_metadata":{"authors":[{"family":"Szabo","given":"Peter A."},{"family":"Dogra","given":"Pranay"},{"family":"Gray","given":"Joshua I."},{"family":"Wells","given":"Steven B."},{"family":"Connors","given":"Thomas J."},{"family":"Weisberg","given":"Stuart P."},{"family":"Krupska","given":"Izabela"},{"family":"Matsumoto","given":"Rei"},{"family":"Poon","given":"Maya M.L."},{"family":"Idzikowski","given":"Emma"},{"family":"Morris","given":"Sinead E."},{"family":"Pasin","given":"Chlo\u00e9"},{"family":"Yates","given":"Andrew J."},{"family":"Ku","given":"Amy"},{"family":"Chait","given":"Michael"},{"family":"Davis-Porada","given":"Julia"},{"family":"Guo","given":"Xinzheng V."},{"family":"Zhou","given":"Jing"},{"family":"Steinle","given":"Matthew"},{"family":"Mackay","given":"Sean"},{"family":"Saqi","given":"Anjali"},{"family":"Baldwin","given":"Matthew R."},{"family":"Sims","given":"Peter A."},{"family":"Farber","given":"Donna L."}],"is_preprint":false,"journal":"Immunity","published_at":1617235200.0,"published_day":1,"published_month":4,"published_year":2021},"revised_at":"2026-06-11T16:52:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"6ff3401b-d72c-4940-a00c-3f0792397082","collection_url":"https://cellxgene.cziscience.com/collections/6ff3401b-d72c-4940-a00c-3f0792397082","collection_version_id":"afe5def9-7ce4-43d3-b5eb-661a6267a1bd","consortia":["European Union\u2019s Horizon 2020"],"contact_email":"roland.eils@bihealth.de","contact_name":"Roland Eils","created_at":"2026-06-10T00:53:02+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"8fcf0ccc-67b2-43a3-90be-075f85169bef","dataset_version_id":"edeeadb2-1264-4fea-a0f5-38e3a092a18d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"respiratory airway","ontology_term_id":"UBERON:0001005","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"2f132ec9-24b5-422f-9be0-ccef03b4fe28","dataset_version_id":"a9453b13-b3ce-4c57-acc3-438f9ea7d4d8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is strongly expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.","doi":"10.15252/embj.20105114","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/articles/dataset/Single-cell_RNA-Seq_of_human_primary_lung_and_bronchial_epithelium_cells/11981034/1"},{"link_name":"","link_type":"OTHER","link_url":"https://digital.bihealth.org/"},{"link_name":"","link_type":"OTHER","link_url":"https://data.mendeley.com/datasets/7r2cwbw44m/1"},{"link_name":"","link_type":"OTHER","link_url":"https://eils-lung.cells.ucsc.edu/"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/58028aa8-0ed2-49ca-b60f-15e2ed5989d5"},{"link_name":"EGAS00001004419","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001004419"}],"name":"SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells","published_at":"2022-09-09T20:10:55+00:00","publisher_metadata":{"authors":[{"family":"Lukassen","given":"Soeren"},{"family":"Chua","given":"Robert Lorenz"},{"family":"Trefzer","given":"Timo"},{"family":"Kahn","given":"Nicolas C"},{"family":"Schneider","given":"Marc A"},{"family":"Muley","given":"Thomas"},{"family":"Winter","given":"Hauke"},{"family":"Meister","given":"Michael"},{"family":"Veith","given":"Carmen"},{"family":"Boots","given":"Agnes W"},{"family":"Hennig","given":"Bianca P"},{"family":"Kreuter","given":"Michael"},{"family":"Conrad","given":"Christian"},{"family":"Eils","given":"Roland"}],"is_preprint":false,"journal":"EMBO J","published_at":1589760000.0,"published_day":18,"published_month":5,"published_year":2020},"revised_at":"2026-06-11T16:53:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a98b828a-622a-483a-80e0-15703678befd","collection_url":"https://cellxgene.cziscience.com/collections/a98b828a-622a-483a-80e0-15703678befd","collection_version_id":"5ff5602b-90fb-4004-adb7-7430cf412ff9","consortia":["CZI Cell Science"],"contact_email":"markusbi@med.umich.edu","contact_name":"Markus Bitzer","created_at":"2026-06-09T23:38:24+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0b4a15a7-4e9e-4555-9733-2423e5c66469","dataset_version_id":"dad69d7e-fb52-46cd-88bc-e4926efcacce","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"}]}],"description":"Tumor-nephrectomy samples","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/29ed827b-c539-4f4c-bb6b-ce8f9173dfb7"}],"name":"HCA kidney seed network: University of Michigan","published_at":"2022-12-20T19:25:18+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:52:34+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"43d4bb39-21af-4d05-b973-4c1fed7b916c","collection_url":"https://cellxgene.cziscience.com/collections/43d4bb39-21af-4d05-b973-4c1fed7b916c","collection_version_id":"83fecbfa-0b3d-4ce2-8b65-203315110f2e","consortia":[],"contact_email":"raymond.cho@ucsf.edu","contact_name":"Raymond J. Cho","created_at":"2026-06-10T02:47:40+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"f512b8b6-369d-4a85-a695-116e0806857f","dataset_version_id":"688f626d-bb26-40dd-8465-83022a5b2c5f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"skin of prepuce of penis","ontology_term_id":"UBERON:0001471","tissue_type":"tissue"},{"label":"skin of scalp","ontology_term_id":"UBERON:8300000","tissue_type":"tissue"},{"label":"skin of trunk","ontology_term_id":"UBERON:0001085","tissue_type":"tissue"}]}],"description":"Perturbations in the transcriptional programs specifying epidermal differentiation cause diverse skin pathologies ranging from impaired barrier function to inflammatory skin disease. However, the global scope and organization of this complex cellular program remain undefined. Here we report single-cell RNA sequencing profiles of 92,889 human epidermal cells from 9 normal and 3 inflamed skin samples. Transcriptomics-derived keratinocyte subpopulations reflect classic epidermal strata but also sharply compartmentalize epithelial functions such as cell-cell communication, inflammation, and WNT pathway modulation. In keratinocytes, \u223c12% of assessed transcript expression varies in coordinate patterns, revealing undescribed gene expression programs governing epidermal homeostasis. We also identify molecular fingerprints of inflammatory skin states, including S100 activation in the interfollicular epidermis of normal scalp, enrichment of a CD1C+CD301A+ myeloid dendritic cell population in psoriatic epidermis, and IL1\u03b2hiCCL3hiCD14+ monocyte-derived macrophages enriched in foreskin. This compendium of RNA profiles provides a critical step toward elucidating epidermal diseases of development, differentiation, and inflammation.","doi":"10.1016/j.celrep.2018.09.006","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=human-epidermis"},{"link_name":"EGAS00001002927","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001002927"}],"name":"Transcriptional Programming of Normal and Inflamed Human Epidermis at Single-Cell Resolution","published_at":"2022-10-31T18:01:30+00:00","publisher_metadata":{"authors":[{"family":"Cheng","given":"Jeffrey B."},{"family":"Sedgewick","given":"Andrew J."},{"family":"Finnegan","given":"Alex I."},{"family":"Harirchian","given":"Paymann"},{"family":"Lee","given":"Jerry"},{"family":"Kwon","given":"Sunjong"},{"family":"Fassett","given":"Marlys S."},{"family":"Golovato","given":"Justin"},{"family":"Gray","given":"Matthew"},{"family":"Ghadially","given":"Ruby"},{"family":"Liao","given":"Wilson"},{"family":"Perez White","given":"Bethany E."},{"family":"Mauro","given":"Theodora M."},{"family":"Mully","given":"Thaddeus"},{"family":"Kim","given":"Esther A."},{"family":"Sbitany","given":"Hani"},{"family":"Neuhaus","given":"Isaac M."},{"family":"Grekin","given":"Roy C."},{"family":"Yu","given":"Siegrid S."},{"family":"Gray","given":"Joe W."},{"family":"Purdom","given":"Elizabeth"},{"family":"Paus","given":"Ralf"},{"family":"Vaske","given":"Charles J."},{"family":"Benz","given":"Stephen C."},{"family":"Song","given":"Jun S."},{"family":"Cho","given":"Raymond J."}],"is_preprint":false,"journal":"Cell 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We studied an elderly man with a hereditary, progressive dementing disorder of unclear etiology. Standard genetic testing for leukodystrophy and other neurodegenerative conditions was negative. Brain autopsy revealed classic features of adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP), including confluent white matter degeneration with axonal spheroids and pigmented glial cells in the affected white matter, consistent with CSF1R-RD. Subsequent long-read sequencing identified a novel deletion in CSF1R that was not detectable with short-read exome sequencing. To gain insight into potential mechanisms underlying white matter degeneration in CSF1R-RD, we studied multiple brain regions exhibiting varying degrees of white matter pathology. We found decreased CSF1R transcript and protein across brain regions, including intact white matter. Single nuclear RNA sequencing (snRNAseq) identified two disease-associated microglial cell states: lipid-laden microglia (expressing GPNMB, ATG7, LGALS1, LGALS3) and inflammatory microglia (expressing IL2RA, ATP2C1, FCGBP, VSIR, SESN3), along with a small population of CD44+ peripheral monocyte-derived macrophages exhibiting migratory and phagocytic signatures. GPNMB+ lipid-laden microglia with ameboid morphology represented the end-stage disease microglia state. Disease-associated oligodendrocytes exhibited cell stress signatures and dysregulated apoptosis-related genes. Disease-associated oligodendrocyte precursor cells (OPCs) displayed a failure in their differentiation into mature myelin-forming oligodendrocytes, as evidenced by upregulated LRP1, PDGFRA, SOX5, NFIA, and downregulated NKX2-2, NKX6.2, SOX4, SOX8, TCF7L2, YY1, ZNF488. Overall, our findings highlight microglia\u2013oligodendroglia crosstalk in demyelination, with CSF1R dysfunction promoting phagocytic and inflammatory microglia states, an arrest in OPC differentiation, and oligodendrocyte depletion.","doi":"10.1186/s40478-024-01853-5","is_pre_analysis":false,"links":[{"link_name":"GSE267301","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267301"}],"name":"Deciphering glial contributions to CSF1R-related disorder via single-nuclear transcriptomic profiling","published_at":"2024-10-09T16:45:07+00:00","publisher_metadata":{"authors":[{"family":"Pan","given":"Jie"},{"family":"Fores-Martos","given":"Jaume"},{"family":"Delpirou Nouh","given":"Claire"},{"family":"Jensen","given":"Tanner D."},{"family":"Vallejo","given":"Kristen"},{"family":"Cayrol","given":"Romain"},{"family":"Ahmadian","given":"Saman"},{"family":"Ashley","given":"Euan A."},{"family":"Greicius","given":"Michael 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V1","ontology_term_id":"EFO:0022857"}],"dataset_id":"1e191a00-65da-4170-b9b7-eb94359d7de4","dataset_version_id":"86ea4533-fc57-4087-9104-4ed781796841","disease":[{"label":"colorectal cancer","ontology_term_id":"MONDO:0005575"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"right colon","ontology_term_id":"UBERON:0008972","tissue_type":"tissue"}]},{"assay":[{"label":"Visium Spatial Gene Expression V1","ontology_term_id":"EFO:0022857"}],"dataset_id":"15b98664-a52b-4877-aed9-03f4d73d2d2c","dataset_version_id":"4f43fbfe-b88a-4010-9d5f-359afafe80e0","disease":[{"label":"colorectal cancer","ontology_term_id":"MONDO:0005575"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"rectum","ontology_term_id":"UBERON:0001052","tissue_type":"tissue"}]}],"description":"The consensus molecular subtypes (CMS) of colorectal cancer (CRC) is the most widely-used gene expression-based classification and has contributed to a better understanding of disease heterogeneity and prognosis. Nevertheless, CMS intratumoral heterogeneity restricts its clinical application, stressing the necessity of further characterizing the composition and architecture of CRC. Here, we used Spatial Transcriptomics (ST) in combination with single-cell RNA sequencing (scRNA-seq) to decipher the spatially resolved cellular and molecular composition of CRC. In addition to mapping the intratumoral heterogeneity of CMS and their microenvironment, we identified cell communication events in the tumor-stroma interface of CMS2 carcinomas. This includes tumor growth-inhibiting as well as -activating signals, such as the potential regulation of the ETV4 transcriptional activity by DCN or the PLAU-PLAUR ligand-receptor interaction. Our study illustrates the potential of ST to resolve CRC molecular heterogeneity and thereby help advance personalized therapy.","doi":"10.1038/s41698-023-00488-4","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/alberto-valdeolivas/ST_CRC_CMS/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://zenodo.org/records/7760264"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/7744244"}],"name":"Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics","published_at":"2024-08-15T15:41:10+00:00","publisher_metadata":{"authors":[{"family":"Valdeolivas","given":"Alberto"},{"family":"Amberg","given":"Bettina"},{"family":"Giroud","given":"Nicolas"},{"family":"Richardson","given":"Marion"},{"family":"G\u00e1lvez","given":"Eric J. C."},{"family":"Badillo","given":"Solveig"},{"family":"Julien-Laferri\u00e8re","given":"Alice"},{"family":"T\u00far\u00f3s","given":"Demeter"},{"family":"Voith von Voithenberg","given":"Lena"},{"family":"Wells","given":"Isabelle"},{"family":"Pesti","given":"Benedek"},{"family":"Lo","given":"Amy A."},{"family":"Y\u00e1ng\u00fcez","given":"Emilio"},{"family":"Das Thakur","given":"Meghna"},{"family":"Bscheider","given":"Michael"},{"family":"Sultan","given":"Marc"},{"family":"Kumpesa","given":"Nadine"},{"family":"Jacobsen","given":"Bj\u00f6rn"},{"family":"Bergauer","given":"Tobias"},{"family":"Saez-Rodriguez","given":"Julio"},{"family":"Rottenberg","given":"Sven"},{"family":"Schwalie","given":"Petra C."},{"family":"Hahn","given":"Kerstin"}],"is_preprint":false,"journal":"npj Precis. Onc.","published_at":1704844800.0,"published_day":10,"published_month":1,"published_year":2024},"revised_at":"2026-06-11T16:52:37+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0a77d4c0-d5d0-40f0-aa1a-5e1429bcbd7e","collection_url":"https://cellxgene.cziscience.com/collections/0a77d4c0-d5d0-40f0-aa1a-5e1429bcbd7e","collection_version_id":"bf6c8c81-4e6d-4f14-9186-38995259b8d5","consortia":["CZI Cell Science","European Union\u2019s Horizon 2020"],"contact_email":"fabian.theis@helmholtz-muenchen.de","contact_name":"Fabian Theis","created_at":"2026-06-10T11:45:22+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"db4a9ed2-e994-40c1-b7ec-4091fdf7b6c1","dataset_version_id":"a554a5a6-4f8b-46b2-8bb8-c1738d97f8c7","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Sus scrofa domesticus","ontology_term_id":"NCBITaxon:9825"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"3294d050-6eeb-4a00-b24c-71aacc9b777f","dataset_version_id":"d9a1c2e4-5dd2-4afa-96b1-98876ff00f51","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"07f14e26-ff0d-43c4-bfe3-bf1a94dc73c3","dataset_version_id":"f307b57e-3fe9-4c29-b0ea-8a5be102a572","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"}]}],"description":"Pancreatic islets of Langerhans secrete hormones to regulate systemic glucose levels. Emerging evidence suggests that islet cells are functionally heterogeneous to allow a fine-tuned and efficient endocrine response to physiological changes. A precise description of the molecular basis of this heterogeneity, in particular linking animal models to human islets, is an important step towards identifying the factors critical for endocrine cell function in physiological and pathophysiological conditions. In this study, we used single-cell RNA sequencing to profile more than 50\u2019000 endocrine cells isolated from healthy human, pig and mouse pancreatic islets and characterize transcriptional heterogeneity and evolutionary conservation of those cells across the three species. We systematically delineated endocrine cell types and \u03b1- and \u03b2-cell heterogeneity through prior knowledge- and data-driven gene sets shared across species, which altogether capture common and differential cellular properties, transcriptional dynamics and putative driving factors of state transitions. We showed that global endocrine expression profiles correlate, and that critical identity and functional markers are shared between species, while only approximately 20% of cell type enriched expression is conserved. We resolved distinct human \u03b1- and \u03b2-cell states that form continuous transcriptional landscapes. These states differentially activate maturation and hormone secretion programs, which are related to regulatory hormone receptor expression, signaling pathways and different types of cellular stress responses. Finally, we mapped mouse and pig cells to the human reference and observed that the spectrum of human \u03b1- and \u03b2-cell heterogeneity and aspects of such functional gene expression are better recapitulated in the pig than mouse data. Here, we provide a high-resolution transcriptional map of healthy human islet cells and their murine and porcine counterparts, which is easily queryable via an online interface. This comprehensive resource informs future efforts that focus on pancreatic endocrine function, failure and regeneration, and enables to assess molecular conservation in islet biology across species for translational purposes.","doi":"10.1016/j.molmet.2022.101595","is_pre_analysis":false,"links":[{"link_name":"GSE128565","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE128565"},{"link_name":"GSE198623","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE198623"}],"name":"A transcriptional cross species map of pancreatic islet cells","published_at":"2022-09-20T21:12:08+00:00","publisher_metadata":{"authors":[{"family":"Tritschler","given":"Sophie"},{"family":"Thomas","given":"Moritz"},{"family":"B\u00f6ttcher","given":"Anika"},{"family":"Ludwig","given":"Barbara"},{"family":"Schmid","given":"Janine"},{"family":"Schubert","given":"Undine"},{"family":"Kemter","given":"Elisabeth"},{"family":"Wolf","given":"Eckhard"},{"family":"Lickert","given":"Heiko"},{"family":"Theis","given":"Fabian J."}],"is_preprint":false,"journal":"Molecular Metabolism","published_at":1669852800.0,"published_day":1,"published_month":12,"published_year":2022},"revised_at":"2026-06-11T16:52:39+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"113a558a-e96e-4643-81db-140e95c58578","collection_url":"https://cellxgene.cziscience.com/collections/113a558a-e96e-4643-81db-140e95c58578","collection_version_id":"412287ca-3acc-484f-a227-12e3f87b6a81","consortia":[],"contact_email":"sten.linnarsson@ki.se","contact_name":"Sten Linnarsson","created_at":"2026-06-10T00:50:10+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"21722308-5091-4b63-9c07-4f116ab9a7b3","dataset_version_id":"d45b4ce6-9725-4d79-b97a-70a44158bdbf","disease":[{"label":"glioblastoma","ontology_term_id":"MONDO:0018177"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"right temporal lobe","ontology_term_id":"UBERON:0002809","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"145dcf6a-2461-4fa3-a0af-7fc56db0bd33","dataset_version_id":"66e7fd4d-d2db-464d-9fad-6eda97aff2e1","disease":[{"label":"glioblastoma","ontology_term_id":"MONDO:0018177"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"right temporal lobe","ontology_term_id":"UBERON:0002809","tissue_type":"tissue"}]}],"description":"Human glioblastoma samples were collected with informed consent from two patients with  ethical approval from the Swedish Ethical Review Authority. Systematic sampling was done at multiple distances from the center of the tumor core in four different directions (anterior, posterior, superior, inferior). Multisampling was done based on 5-ALA fluorescence in order to eliminate brain shift bias. Tissue samples were dissociated and suspension quality was analyzed using a hematocytometer. Two to three replicates per sample were processed for scRNAseq with the 10X Genomics V3.1 kits followed by deep sequencing of about 100 000 reads per cell on the Illumina NovasSeq platform.","doi":"10.1101/2023.09.01.555882","is_pre_analysis":false,"links":[],"name":"Single-cell RNA sequencing of glioblastoma cases with tissue sampled from tumor core to macroscopically normal cortex","published_at":"2025-05-06T17:10:01+00:00","publisher_metadata":{"authors":[{"family":"Mossi Albiach","given":"Alejandro"},{"family":"Janusauskas","given":"Jokubas"},{"family":"Jacobsen","given":"Jesper Kjaer"},{"family":"Kapustov\u00e1","given":"Ivana"},{"family":"Karamzadeh","given":"Razieh"},{"family":"Kvedaraite","given":"Egle"},{"family":"Hu","given":"Lijuan"},{"family":"Franck","given":"Marina C. M."},{"family":"Mannens","given":"Camiel"},{"family":"Codeluppi","given":"Simone"},{"family":"Munting","given":"Johannes B."},{"family":"Borm","given":"Lars E."},{"family":"Shamikh","given":"Alia"},{"family":"L\u00f6nnerberg","given":"Peter"},{"family":"Siletti","given":"Kimberly A."},{"family":"Persson","given":"Oscar"},{"family":"Linnarsson","given":"Sten"}],"is_preprint":true,"journal":"bioRxiv","published_at":1693785600.0,"published_day":4,"published_month":9,"published_year":2023},"revised_at":"2026-06-11T16:53:44+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"b953c942-f5d8-434f-9da7-e726ba7c1481","collection_url":"https://cellxgene.cziscience.com/collections/b953c942-f5d8-434f-9da7-e726ba7c1481","collection_version_id":"1916410f-d8e0-4486-9157-a74f64180cc0","consortia":[],"contact_email":"icobos@stanford.edu","contact_name":"Inma Cobos","created_at":"2026-06-09T23:49:29+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"9813a1d4-d107-459e-9b2e-7687be935f69","dataset_version_id":"9b87c411-2e17-4de4-918b-e2c476ad48a7","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"prefrontal cortex","ontology_term_id":"UBERON:0000451","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"85c60876-7f35-40c5-a256-7808d84c6ba5","dataset_version_id":"5015051f-abc4-4034-9374-eada74e37c99","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"prefrontal cortex","ontology_term_id":"UBERON:0000451","tissue_type":"tissue"}]}],"description":"Tau aggregation in neurofibrillary tangles (NFTs) is closely associated with neurodegeneration and cognitive decline in Alzheimer\u2019s disease (AD). However, the molecular signatures that distinguish between aggregation-prone and aggregation-resistant cell states are unknown. We developed a FACS-based method for the high-throughput isolation of individual somas with NFTs from frozen human brain and profiled the transcriptomes of 63,110 somas with or without NFTs from the prefrontal cortex of eight Braak VI AD donors, and 57,534 somas from eight age-matched healthy donors. We quantified the susceptibility of 20 neocortical subtypes for NFT formation and cell death, and identified the shared and cell-type-specific signatures associated with NFTs. NFT-bearing neurons shared a marked upregulation of synaptic transmission-related genes, including a core set of 63 genes enriched for synaptic vesicle cycling. Oxidative phosphorylation and mitochondrial dysfunction were highly cell-type dependent. Apoptosis was only modestly enriched, and the susceptibilities of NFT-bearing and NFT-free neurons for death were highly similar. Our analysis suggests that NFTs represent cell-type-specific compensatory responses to stress and synaptic dysfunction. We provide a resource for biomarker discovery and investigation of tau-dependent and tau-independent mechanisms of neurodegeneration.  \n\nNote: FACS sorted populations: MAP2+/AT8- somas from AD donors (aka MAP2 or NFT-free);  MAP2+/AT8+ somas from AD donors (aka AT8 or NFT-bearing); MAP2+ somas from healthy controls (aka MAP2control)","doi":"10.1016/j.neuron.2022.06.021","is_pre_analysis":false,"links":[{"link_name":"Single-soma isolation protocol","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/isolation-of-single-somas-from-postmortem-fresh-fr-bp2l64o2dvqe/v1"},{"link_name":"GSE129308","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129308"}],"name":"Single-soma transcriptomics of tangle-bearing neurons in Alzheimer\u2019s disease","published_at":"2021-05-19T19:58:31+00:00","publisher_metadata":{"authors":[{"family":"Otero-Garcia","given":"Marcos"},{"family":"Mahajani","given":"Sameehan 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This collection only contains RNA derived modalities (RNA, SCENIC, TF activity). Link to the visualization of ATAC modality can be found in our paper.\n\n\n\nFor TG data:\nThe UMAP structure was computed from the latent representation from scGLUE model by passing the scANVI latent representation as the embedding to train the model to help with the integration. \n\nWith scGLUE, we could extract the latent representation of the feature space (stored in .varm) for down stream analysis of the gene expression and chromatin accessibility. 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Using single nucleus RNA sequencing (snRNAseq), we characterized the transcriptome of 880,000 nuclei from 18 control and 61 failing, non-ischemic human hearts with pathogenic variants in DCM and ACM genes or idiopathic disease. We performed genotype-stratified analyses of the ventricular cell lineages and transcriptional states. The resultant DCM and ACM ventricular cell atlas demonstrated distinct right and left ventricular responses, highlighting genotype-associated pathways, intercellular interactions, and differential gene expression at single cell resolution. 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Peripheral blood mononuclear cells (PBMCs) from a single donor were used to assess analytical performance. Key features such as sample compatibility, cost, and experimental duration were also compared. Notably, superior analytical performance was demonstrated by the Chromium Fixed RNA Profiling kit from 10x Genomics, which uniquely features probe hybridization for transcript detection. Additionally, the Rhapsody WTA kit from Becton Dickinson provided a cost-effective balance of performance and expense per cell. With a rich dataset of 169,262 cells, this work provides a basis for differentiating commercial scRNA-seq technologies, which is intended to facilitate the effective application and further methodological development of single cell transcriptomics.","doi":"10.1093/nar/gkae1186","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/danledinh/scRNAseq-repo"},{"link_name":"PRJNA1106903","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1106903"},{"link_name":"zenodo.org","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.13910292"}],"name":"Comparative Analysis of Commercial Single-Cell RNA Sequencing Technologies","published_at":"2024-07-18T20:10:12+00:00","publisher_metadata":{"authors":[{"family":"De\u00a0Simone","given":"Marco"},{"family":"Hoover","given":"Jonathan"},{"family":"Lau","given":"Julia"},{"family":"Bennett","given":"Hayley\u00a0M"},{"family":"Wu","given":"Bing"},{"family":"Chen","given":"Cynthia"},{"family":"Menon","given":"Hari"},{"family":"Au-Yeung","given":"Amelia"},{"family":"Lear","given":"Sean"},{"family":"Vaidya","given":"Samir"},{"family":"Shi","given":"Minyi"},{"family":"Lund","given":"Jessica\u00a0M"},{"family":"Xavier-Magalh\u00e3es","given":"Ana"},{"family":"Liang","given":"Yuxin"},{"family":"Kurdoglu","given":"Ahmet"},{"family":"O\u2019Gorman","given":"William\u00a0E"},{"family":"Modrusan","given":"Zora"},{"family":"Le","given":"Daniel"},{"family":"Darmanis","given":"Spyros"}],"is_preprint":false,"journal":"Nucleic Acids Research","published_at":1736553600.0,"published_day":11,"published_month":1,"published_year":2025},"revised_at":"2026-08-17T23:55:18+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5c868b6f-62c5-4532-9d7f-a346ad4b50a7","collection_url":"https://cellxgene.cziscience.com/collections/5c868b6f-62c5-4532-9d7f-a346ad4b50a7","collection_version_id":"f522ebc2-636e-4485-917b-1dbfc19e0ad4","consortia":[],"contact_email":"xavier@molbio.mgh.harvard.edu","contact_name":"Ramnik J. 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While most previous studies have focused on the breast epithelial system4-6, many of the non-epithelial cell types remain understudied. Here, we constructed a comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics data profiled 714,331 cells from 126 women, and 120,024 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data revealed abundant pericyte, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. 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v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"1873a18a-66fd-4a4d-8277-a872c93f5b59","dataset_version_id":"34702b40-d0ac-4ec2-8871-776ca012efd0","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"primary biliary cholangitis","ontology_term_id":"MONDO:0005388"},{"label":"primary sclerosing cholangitis","ontology_term_id":"MONDO:0013433"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"0c9a8cfb-6649-4d52-b418-6d8e56bd7afe","dataset_version_id":"58821f45-6468-4766-af0b-8cb164ae71d7","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"02792605-4760-4023-82ad-40fc4458a5db","dataset_version_id":"ff713455-e6b7-45b3-b2dd-1c9dd26251f6","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"primary biliary cholangitis","ontology_term_id":"MONDO:0005388"},{"label":"primary sclerosing cholangitis","ontology_term_id":"MONDO:0013433"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]}],"description":"Background:  Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease characterized by bile retention, biliary tree destruction, and progressive fibrosis leading to end stage liver disease and transplantation. There is an unmet need to understand the cellular composition of the PSC liver and how it underlies disease pathogenesis. We generated a comprehensive atlas of the PSC liver in comparison to a primary biliary cholangitis (PBC) and reference healthy liver dataset using multiple multi-omic modalities and functional validation. Methods: We employed single-cell (sc) RNA-seq (47,156 cells), single-nucleus (sn) RNA-seq (23,000 nuclei) and spatial transcriptomics (1 sample by 10x Visium and 5 samples with multi-region profiling by Nanostring GeoMx Digital Spatial Profiler) to profile the cellular ecosystem in 10 patients with PSC. Transcriptomic profiles were compared to 24 neurologically deceased donor livers (107,542 cells) and spatial transcriptomics controls, 18,240 cells and 20,202 nuclei from 3 patients with PBC, and publicly available scRNA-seq data from 5 uninjured, 2 NAFLD, 2 ALD, and 1 PBC liver samples. Flow cytometry and intracellular cytokine staining was performed to validate PSC-specific differences in immune cell phenotype and function. Results: PSC explants with cirrhosis of the liver parenchyma and prominent periductal fibrosis contained a population of hepatocytes expressing a cholangiocyte-like phenotype. These hepatocytes were surrounded by diverse immune cell populations, including monocyte-like macrophages, liver-resident and circulating natural killer cells. PSC-associated cholangiocytes, hepatic stellate cells, and endothelial cells expressed chemokine and cytokine transcripts typically involved in immune cell recruitment. As well, expanded CD4+ T cells, dendritic cells and neutrophils in the PSC liver expressed the corresponding receptors to these chemokines and cytokines, suggesting potential recruitment. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional and downregulated inflammatory response to LPS and IFN-\u0194 stimulation.","doi":"10.1016/j.jhep.2023.12.023","is_pre_analysis":false,"links":[{"link_name":"MacParland et al. (2018) Nature","link_type":"OTHER","link_url":"https://www.nature.com/articles/s41467-018-06318-7"},{"link_name":"GSE240429","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE240429"},{"link_name":"GSE115469","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115469"},{"link_name":"GSE243977","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE243977"},{"link_name":"GSE247128","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE247128"},{"link_name":"GSE245620","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE245620"}],"name":"Single-cell and spatial transcriptomics characterisation of the immunological landscape in the healthy and PSC human liver","published_at":"2024-02-23T19:49:59+00:00","publisher_metadata":{"authors":[{"family":"Andrews","given":"Tallulah S."},{"family":"Nakib","given":"Diana"},{"family":"Perciani","given":"Catia T."},{"family":"Ma","given":"Xue Zhong"},{"family":"Liu","given":"Lewis"},{"family":"Winter","given":"Erin"},{"family":"Camat","given":"Damra"},{"family":"Chung","given":"Sai W."},{"family":"Lumanto","given":"Patricia"},{"family":"Manuel","given":"Justin"},{"family":"Mangroo","given":"Shantel"},{"family":"Hansen","given":"Bettina"},{"family":"Arpinder","given":"Bal"},{"family":"Thoeni","given":"Cornelia"},{"family":"Sayed","given":"Blayne"},{"family":"Feld","given":"Jordan"},{"family":"Gehring","given":"Adam"},{"family":"Gulamhusein","given":"Aliya"},{"family":"Hirschfield","given":"Gideon M."},{"family":"Ricciuto","given":"Amanda"},{"family":"Bader","given":"Gary D."},{"family":"McGilvray","given":"Ian D."},{"family":"MacParland","given":"Sonya"}],"is_preprint":false,"journal":"Journal of Hepatology","published_at":1714521600.0,"published_day":1,"published_month":5,"published_year":2024},"revised_at":"2026-06-11T16:53:49+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"10bf5c50-8d85-4c5f-94b4-22c1363d9f31","collection_url":"https://cellxgene.cziscience.com/collections/10bf5c50-8d85-4c5f-94b4-22c1363d9f31","collection_version_id":"ea2e2701-7a44-4d20-abb6-ae1a17260479","consortia":[],"contact_email":"ulisetorr13@gmail.com","contact_name":"Ulises Torres-Flores","created_at":"2026-06-10T13:45:50+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"be884a28-0eac-4eca-9c23-1294a93cf56e","dataset_version_id":"206a2e16-8f04-4493-a9ea-33377e6d53b3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"pilocytic astrocytoma","ontology_term_id":"MONDO:0016691"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"}]}],"description":"Cancer tumors are composed by a wide variety of cells with genetic and transcriptional alterations accumulated throughout tumor progression. This intra-tumoral heterogeneity provides adaptability of the tumor. Cell niches enriched with transcriptional signatures for cell renewal, adaptation and resistance to DNA damage induced by radiation (radiotherapy resistance) have been identified within some cancer tumors. Therefore, it seems that intra-tumoral heterogeneity imposes deep challenges to current therapeutic treatments. \nTumors of the central nervous system are the most common solid tumors during childhood and are in the top-two causes of cancer-related death in children worldwide. Gliomas arise from glial precursor cells that are present in the brain and spinal cord and astrocytoma is the most commonly diagnosed type of glioma in children. Despite similar origin, astrocytomas behave differently depending on their location. Pilocytic astrocytoma that arise in cerebellum are more resilient and display a higher relapse degree after removal compared to those ones that arise in cerebrum. We will compare the transcritome of single nuclei from pediatric pilocytic astrocytoma from cerebellum in two time points (i.e., newly diagnosed vs relapse) plus healthy tissues. We predict that cells that produce tumor relapse will be present in both time points. Therefore, based on their transcriptional profiles, we will be able to identify them. This information will provide a deep knowledge about tumor relapse that can be extrapolated to other tumors and will offer RNA biomarkers for therapeutic purposes.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/575c0ad9-c78e-469b-9fdf-9a68dd881137"}],"name":"Intratumoral heterogeneity in recurrent pediatric pilocytic astrocytomas","published_at":"2023-03-27T22:04:26+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:53:49+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d1e0e64d-6d2a-4a3e-b7f4-43ed909a9d9c","collection_url":"https://cellxgene.cziscience.com/collections/d1e0e64d-6d2a-4a3e-b7f4-43ed909a9d9c","collection_version_id":"16191bbd-5306-4ffe-97d9-ad5b0a0ff00d","consortia":["CZI Cell Science"],"contact_email":"irene.gallego@svi.edu.au","contact_name":"Irene Gallego Romero","created_at":"2026-06-10T15:14:31+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"ca7d95ac-53aa-4a94-8c76-300c608ce6a0","dataset_version_id":"6a322de5-4cc6-43f5-b35d-6f0c246fb297","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"b3875c91-55a6-4187-af6f-486505de025d","dataset_version_id":"770a441b-b903-4d22-8873-09b1abfd797a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"55ec1734-60b6-496e-87ad-6f2f44229422","dataset_version_id":"ef8a4400-b2f9-4724-8f19-b94c76c53f8a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Island Southeast Asia (ISEA) remains consistently underrepresented in human genomic resources despite its exceptional ancestral and lifestyle diversity. The interplay between the region\u2019s complex population history and its environmental variation provide a window into how ancestry and environment jointly shape the human immune system. Here we report the generation of single-cell PBMC profiles from 199 Indonesians sampled across four communities in the islands of Bali and New Guinea. These groups capture diversity in regional genetic ancestries (East Asian-like and Papuan-like) and lifestyle contrasts (urban versus rural communities in Bali; highland versus lowland communities in New Guinea). We identify over 4,000 expression quantitative trait loci (eQTLs) across nine immune cell types, including eQTLs driven by introgression from both Neanderthals and Denisovans at genes such as IL7R, HLA-E, or STAT2. We also find evidence of local ancestry driving gene-by-environment interactions at pathogen receptors such as MARCO, although the majority of gene-by-environment interactions are not driven by differences in genetic structure between populations. Beyond direct genetic effects, we construct gene co-expression networks that consistently identify environmental signatures, as well as T-cell receptor repertoires that distinguish specific communities, with excess representation of interferon-stimulated genes in rural, but not urban samples. This work establishes a framework for population-aware functional genomics in understudied regions and highlights how ancestral and environmental diversity jointly shape human immunity in this globally important yet underrepresented region.","doi":"10.64898/2026.02.15.704933","is_pre_analysis":false,"links":[],"name":"Ancestral and environmental diversity shape the immune landscape in Indonesia","published_at":"2026-02-13T17:43:21+00:00","publisher_metadata":{"authors":[{"family":"Fachrul","given":"Muhamad"},{"family":"Sukonthamarn","given":"Pongsakorn"},{"family":"Kusuma","given":"Pradiptajati"},{"family":"Novita","given":"Monika Meili"},{"family":"Alvim","given":"Isabela"},{"family":"Apriyana","given":"Isabella"},{"family":"Crenna-Darusallam","given":"Chelzie"},{"family":"Christian","given":"Andreas"},{"family":"Groudko","given":"Alice"},{"family":"Kendle","given":"Robert"},{"family":"Limardi","given":"Prisca Cynthia"},{"family":"Mee","given":"Evan D"},{"family":"Oktavianthi","given":"Sukma"},{"family":"Peter","given":"Lance M"},{"family":"Priliani","given":"Lidwina"},{"family":"Utami","given":"Bertha Letizia"},{"family":"Sokoy","given":"Fredik"},{"family":"Frank","given":"Simon Abdi K"},{"family":"Wihandani","given":"Desak Made"},{"family":"Dewi","given":"Ni Nyoman Ayu"},{"family":"Darwinata","given":"Agus Eka"},{"family":"Cox","given":"Murray P"},{"family":"Banovich","given":"Nicholas E"},{"family":"Sudoyo","given":"Herawati"},{"family":"Malik","given":"Safarina G"},{"family":"Gallego Romero","given":"Irene"}],"is_preprint":true,"journal":"bioRxiv","published_at":1771113600.0,"published_day":15,"published_month":2,"published_year":2026},"revised_at":"2026-06-11T16:53:49+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"32f2fd23-ec74-486f-9544-e5b2f41725f5","collection_url":"https://cellxgene.cziscience.com/collections/32f2fd23-ec74-486f-9544-e5b2f41725f5","collection_version_id":"db36d69b-fec5-49af-a53c-239546972e24","consortia":["CZI Cell Science","Wellcome HCA Strategic Science Support"],"contact_email":"rv4@sanger.ac.uk","contact_name":"Roser Vento-Tormo","created_at":"2026-06-10T01:02:21+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"9ddea8d9-cc4c-420a-90f6-880996f808d4","dataset_version_id":"e9c1bce2-a784-4acb-bd02-31e05305eb8a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"endometrium","ontology_term_id":"UBERON:0001295","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"968885c5-b652-48d9-9006-c34b5fc1c07a","dataset_version_id":"b1899c6c-b1a6-4340-9df1-b62a00a6e8af","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"endometrium","ontology_term_id":"UBERON:0001295","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"76150f40-1989-4977-9e23-696e72d59d9e","dataset_version_id":"006980b4-1d18-4a37-a268-8ed2845cb4d2","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"endometrium","ontology_term_id":"UBERON:0001295","tissue_type":"organoid"}]}],"description":"The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated dense single-cell and spatial reference maps of the human uterus and three-dimensional endometrial organoid cultures. We dissect the signaling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids reveals the pathways and cell states regulating differentiation of the secretory and ciliated lineages both in vivo and in vitro. In vitro downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. We utilize our cellular maps to deconvolute bulk data from endometrial cancers and endometriotic lesions, illuminating the cell types dominating in each of these disorders. These mechanistic insights provide a platform for future development of treatments for common conditions including endometriosis and endometrial carcinoma.","doi":"10.1038/s41588-021-00972-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/2b38025d-a5ea-4c0f-b22e-367824bcaf4c"},{"link_name":"","link_type":"OTHER","link_url":"https://www.reproductivecellatlas.org/"},{"link_name":"E-MTAB-10287","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10287"},{"link_name":"E-MTAB-9260","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9260"},{"link_name":"E-MTAB-10283","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10283"},{"link_name":"EGAD00001007909","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001007909"}],"name":"Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro","published_at":"2022-05-27T10:01:37+00:00","publisher_metadata":{"authors":[{"family":"Garcia-Alonso","given":"Luz"},{"family":"Handfield","given":"Louis-Fran\u00e7ois"},{"family":"Roberts","given":"Kenny"},{"family":"Nikolakopoulou","given":"Konstantina"},{"family":"Fernando","given":"Ridma C."},{"family":"Gardner","given":"Lucy"},{"family":"Woodhams","given":"Benjamin"},{"family":"Arutyunyan","given":"Anna"},{"family":"Polanski","given":"Krzysztof"},{"family":"Hoo","given":"Regina"},{"family":"Sancho-Serra","given":"Carmen"},{"family":"Li","given":"Tong"},{"family":"Kwakwa","given":"Kwasi"},{"family":"Tuck","given":"Elizabeth"},{"family":"Lorenzi","given":"Valentina"},{"family":"Massalha","given":"Hassan"},{"family":"Prete","given":"Martin"},{"family":"Kleshchevnikov","given":"Vitalii"},{"family":"Tarkowska","given":"Aleksandra"},{"family":"Porter","given":"Tarryn"},{"family":"Mazzeo","given":"Cecilia Icoresi"},{"family":"van Dongen","given":"Stijn"},{"family":"Dabrowska","given":"Monika"},{"family":"Vaskivskyi","given":"Vasyl"},{"family":"Mahbubani","given":"Krishnaa T."},{"family":"Park","given":"Jong-eun"},{"family":"Jimenez-Linan","given":"Mercedes"},{"family":"Campos","given":"Lia"},{"family":"Kiselev","given":"Vladimir Yu."},{"family":"Lindskog","given":"Cecilia"},{"family":"Ayuk","given":"Paul"},{"family":"Prigmore","given":"Elena"},{"family":"Stratton","given":"Michael R."},{"family":"Saeb-Parsy","given":"Kourosh"},{"family":"Moffett","given":"Ashley"},{"family":"Moore","given":"Luiza"},{"family":"Bayraktar","given":"Omer A."},{"family":"Teichmann","given":"Sarah A."},{"family":"Turco","given":"Margherita Y."},{"family":"Vento-Tormo","given":"Roser"}],"is_preprint":false,"journal":"Nat Genet","published_at":1638316800.0,"published_day":1,"published_month":12,"published_year":2021},"revised_at":"2026-06-11T16:53:50+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"b0cf0afa-ec40-4d65-b570-ed4ceacc6813","collection_url":"https://cellxgene.cziscience.com/collections/b0cf0afa-ec40-4d65-b570-ed4ceacc6813","collection_version_id":"8588d955-fd30-4de7-b039-335a4a60d8c7","consortia":["CZI Cell Science"],"contact_email":"rsatija@nygenome.org","contact_name":"Rahul Satija","created_at":"2026-06-10T03:32:13+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ed5d841d-6346-47d4-ab2f-7119ad7e3a35","dataset_version_id":"4078abd1-063d-4b35-aa04-324dddf8244e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce \u201cweighted-nearest neighbor\u201d analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). 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Functional characterization of prostate epithelial populations isolated with individual cell surface markers has failed to provide a consensus on the anatomical and transcriptional identity of proximal prostate progenitors. Here, we use single-cell RNA sequencing to obtain a complete transcriptomic profile of all epithelial cells in the mouse prostate and urethra to objectively identify cellular subtypes. Pan-transcriptomic comparison to human prostate cell types identified a mouse equivalent of human urethral luminal cells, which highly expressed putative prostate progenitor markers. Validation of the urethral luminal cell cluster was performed using immunostaining and flow cytometry. Our data reveal that previously identified facultative progenitors marked by Trop2, Sca-1, KRT4, and PSCA are actually luminal epithelial cells of the urethra that extend into the proximal region of the prostate, and are resistant to castration-induced androgen deprivation. Mouse urethral luminal cells were identified to be the equivalent of previously identified human club and hillock cells that similarly extend into proximal prostate ducts. Benign prostatic hyperplasia (BPH) has long been considered an \"embryonic reawakening,\" but the cellular origin of the hyperplastic growth concentrated in the periurethral region is unclear. We demonstrate an increase in urethral luminal cells within glandular nodules from BPH patients. Urethral luminal cells are further increased in patients treated with a 5-\u03b1 reductase inhibitor. Our data demonstrate that cells of the proximal prostate that express putative progenitor markers, and are enriched by castration in the proximal prostate, are urethral luminal cells and that these cells may play an important role in the etiology of human BPH.","doi":"10.1002/pros.24020","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://strandlab.net/"},{"link_name":"Human Raw Data","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145928"},{"link_name":"Mouse Raw Data","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145929"},{"link_name":"www.gudmap.org","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.25548/16-WM8C"}],"name":"Urethral luminal epithelia are castration-insensitive cells of the proximal prostate","published_at":"2021-07-06T19:44:59+00:00","publisher_metadata":{"authors":[{"family":"Joseph","given":"Diya B."},{"family":"Henry","given":"Gervaise H."},{"family":"Malewska","given":"Alicia"},{"family":"Iqbal","given":"Nida S."},{"family":"Ruetten","given":"Hannah M."},{"family":"Turco","given":"Anne E."},{"family":"Abler","given":"Lisa L."},{"family":"Sandhu","given":"Simran K."},{"family":"Cadena","given":"Mark T."},{"family":"Malladi","given":"Venkat S."},{"family":"Reese","given":"Jeffrey C."},{"family":"Mauck","given":"Ryan J."},{"family":"Gahan","given":"Jeffrey C."},{"family":"Hutchinson","given":"Ryan C."},{"family":"Roehrborn","given":"Claus G."},{"family":"Baker","given":"Linda A."},{"family":"Vezina","given":"Chad M."},{"family":"Strand","given":"Douglas W."}],"is_preprint":false,"journal":"Prostate","published_at":1596240000.0,"published_day":1,"published_month":8,"published_year":2020},"revised_at":"2026-06-11T16:52:58+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"b52eb423-5d0d-4645-b217-e1c6d38b2e72","collection_url":"https://cellxgene.cziscience.com/collections/b52eb423-5d0d-4645-b217-e1c6d38b2e72","collection_version_id":"aa697d95-d43f-46a5-829e-3e152746d36e","consortia":["CZI Cell Science","Wellcome HCA Strategic Science Support"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. Teichmann","created_at":"2026-06-10T00:15:44+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f75f2ff4-2884-4c2d-b375-70de37a34507","dataset_version_id":"e94d03ba-1cb0-44da-8aac-2f6d1098f8ae","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"},{"label":"left cardiac atrium","ontology_term_id":"UBERON:0002079","tissue_type":"tissue"},{"label":"right cardiac atrium","ontology_term_id":"UBERON:0002078","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ed852810-a003-4386-9846-1638362cee39","dataset_version_id":"45479bf3-98ce-4276-a365-44e328460c63","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular 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atrium","ontology_term_id":"UBERON:0002079","tissue_type":"tissue"},{"label":"right cardiac atrium","ontology_term_id":"UBERON:0002078","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"78fd69d2-75e4-4207-819a-563139f273c6","dataset_version_id":"af026d10-dd8d-469a-8c50-b80df216b1cb","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"572f3f3e-d3e4-4d13-8e2b-88215e508481","dataset_version_id":"23ea6682-46f7-4703-8429-dd0d09e55cda","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"},{"label":"left cardiac atrium","ontology_term_id":"UBERON:0002079","tissue_type":"tissue"},{"label":"right cardiac atrium","ontology_term_id":"UBERON:0002078","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"1009f384-b12d-448e-ba9f-1b7d2ecfbb4e","dataset_version_id":"339ace92-680a-4fa4-8d67-5a6dd213c5af","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"},{"label":"left cardiac atrium","ontology_term_id":"UBERON:0002079","tissue_type":"tissue"},{"label":"right cardiac atrium","ontology_term_id":"UBERON:0002078","tissue_type":"tissue"}]}],"description":"Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require deeper understanding of the healthy heart\u2019s molecular processes. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavor. Here, using state-of-the-art analyses of large-scale single-cell and nuclei transcriptomes, we characterise six anatomical adult heart regions (left/right atria and ventricles, apex, interventricular septum). Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, revealing distinct atrial and ventricular subsets with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment we identify cardiac resident macrophages with inflammatory and protective transcriptional signatures. Further, inference of cell-cell interactions highlight different macrophage-fibroblast-cardiomyocyte networks between atria and ventricles that are distinct from skeletal muscle. We expect this reference human cardiac cell atlas to advance mechanistic studies of heart homeostasis and disease.","doi":"10.1038/s41586-020-2797-4","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=heart-cell-atlas"},{"link_name":"ERP123138","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/ERP123138"},{"link_name":"","link_type":"OTHER","link_url":"https://support.10xgenomics.com/spatial-gene-expression/datasets/1.1.0/V1_Human_Heart"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/ad98d3cd-26fb-4ee3-99c9-8a2ab085e737"},{"link_name":"","link_type":"OTHER","link_url":"https://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg38&g=heartCellAtlas&position=default"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://www.teichlab.org/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/cartal/HCA_Heart"},{"link_name":"","link_type":"OTHER","link_url":"https://www.heartcellatlas.org/"}],"name":"Cells of the adult human heart","published_at":"2021-03-23T21:04:08+00:00","publisher_metadata":{"authors":[{"family":"Litvi\u0148ukov\u00e1","given":"Monika"},{"family":"Talavera-L\u00f3pez","given":"Carlos"},{"family":"Maatz","given":"Henrike"},{"family":"Reichart","given":"Daniel"},{"family":"Worth","given":"Catherine L."},{"family":"Lindberg","given":"Eric L."},{"family":"Kanda","given":"Masatoshi"},{"family":"Polanski","given":"Krzysztof"},{"family":"Heinig","given":"Matthias"},{"family":"Lee","given":"Michael"},{"family":"Nadelmann","given":"Emily R."},{"family":"Roberts","given":"Kenny"},{"family":"Tuck","given":"Liz"},{"family":"Fasouli","given":"Eirini S."},{"family":"DeLaughter","given":"Daniel M."},{"family":"McDonough","given":"Barbara"},{"family":"Wakimoto","given":"Hiroko"},{"family":"Gorham","given":"Joshua M."},{"family":"Samari","given":"Sara"},{"family":"Mahbubani","given":"Krishnaa T."},{"family":"Saeb-Parsy","given":"Kourosh"},{"family":"Patone","given":"Giannino"},{"family":"Boyle","given":"Joseph J."},{"family":"Zhang","given":"Hongbo"},{"family":"Zhang","given":"Hao"},{"family":"Viveiros","given":"Anissa"},{"family":"Oudit","given":"Gavin Y."},{"family":"Bayraktar","given":"Omer Ali"},{"family":"Seidman","given":"J. G."},{"family":"Seidman","given":"Christine E."},{"family":"Noseda","given":"Michela"},{"family":"Hubner","given":"Norbert"},{"family":"Teichmann","given":"Sarah A."}],"is_preprint":false,"journal":"Nature","published_at":1608163200.0,"published_day":17,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:53:00+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"20eea6c8-9d64-42c9-9b6f-c11b5249e0e9","collection_url":"https://cellxgene.cziscience.com/collections/20eea6c8-9d64-42c9-9b6f-c11b5249e0e9","collection_version_id":"c0f66abe-cd00-420d-b943-bf33499c4e20","consortia":["CZI Cell Science","Human Cell Atlas (HCA)"],"contact_email":"spott@uchicago.edu","contact_name":"Sebastian Pott","created_at":"2026-06-10T08:02:22+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"2e9d2f32-4cfb-49b5-b990-cbf4c241214e","dataset_version_id":"f35a8c3f-b3a0-4373-a4cd-c937db7f7ec2","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"}]}],"description":"Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits","doi":"10.1038/s41467-023-40505-5","is_pre_analysis":false,"links":[{"link_name":"GSE224997","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE224997"}],"name":"Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation","published_at":"2024-07-01T17:15:54+00:00","publisher_metadata":{"authors":[{"family":"Selewa","given":"Alan"},{"family":"Luo","given":"Kaixuan"},{"family":"Wasney","given":"Michael"},{"family":"Smith","given":"Linsin"},{"family":"Sun","given":"Xiaotong"},{"family":"Tang","given":"Chenwei"},{"family":"Eckart","given":"Heather"},{"family":"Moskowitz","given":"Ivan P."},{"family":"Basu","given":"Anindita"},{"family":"He","given":"Xin"},{"family":"Pott","given":"Sebastian"}],"is_preprint":false,"journal":"Nat Commun","published_at":1692230400.0,"published_day":17,"published_month":8,"published_year":2023},"revised_at":"2026-06-11T16:53:54+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"67d26b1d-2b78-4489-ac5e-0f33909a76cb","collection_url":"https://cellxgene.cziscience.com/collections/67d26b1d-2b78-4489-ac5e-0f33909a76cb","collection_version_id":"604e7279-88fe-4845-a696-bc6d1be3dd2b","consortia":[],"contact_email":"hw12@sanger.ac.uk","contact_name":"Holly Whitfield","created_at":"2025-08-05T19:45:09+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"e95b508e-0275-4b12-82c6-0cda7ee89bf9","dataset_version_id":"85d71c48-fc85-44a0-a476-71561a21ba2e","disease":[{"label":"desmoplastic small round cell tumor","ontology_term_id":"MONDO:0019373"},{"label":"myofibroma","ontology_term_id":"MONDO:0006312"},{"label":"osteosarcoma","ontology_term_id":"MONDO:0009807"},{"label":"rhabdomyosarcoma","ontology_term_id":"MONDO:0005212"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"abdomen","ontology_term_id":"UBERON:0000916","tissue_type":"tissue"},{"label":"craniocervical region","ontology_term_id":"UBERON:0007811","tissue_type":"tissue"},{"label":"genitourinary system","ontology_term_id":"UBERON:0004122","tissue_type":"tissue"},{"label":"limb","ontology_term_id":"UBERON:0002101","tissue_type":"tissue"},{"label":"orbital region","ontology_term_id":"UBERON:0004088","tissue_type":"tissue"},{"label":"pelvis connective tissue","ontology_term_id":"UBERON:0003594","tissue_type":"tissue"},{"label":"thoracic segment connective tissue","ontology_term_id":"UBERON:0003837","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' transcription profiling","ontology_term_id":"EFO:0030004"}],"dataset_id":"b1d02f53-187f-4a40-80e3-d3c0646b7752","dataset_version_id":"59c10b31-7fb6-4712-b631-768e469db426","disease":[{"label":"rhabdomyosarcoma","ontology_term_id":"MONDO:0005212"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"prostate gland","ontology_term_id":"UBERON:0002367","tissue_type":"organoid"},{"label":"scrotum","ontology_term_id":"UBERON:0001300","tissue_type":"organoid"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' transcription profiling","ontology_term_id":"EFO:0030004"}],"dataset_id":"1cb09bb9-bb9d-4264-870d-c1cab521f697","dataset_version_id":"ed440808-09de-4fc6-9a1a-5c15056609dd","disease":[{"label":"Ewing sarcoma","ontology_term_id":"MONDO:0012817"},{"label":"rhabdomyosarcoma","ontology_term_id":"MONDO:0005212"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"craniocervical region","ontology_term_id":"UBERON:0007811","tissue_type":"tissue"},{"label":"genitourinary system","ontology_term_id":"UBERON:0004122","tissue_type":"tissue"},{"label":"limb","ontology_term_id":"UBERON:0002101","tissue_type":"tissue"},{"label":"orbital region","ontology_term_id":"UBERON:0004088","tissue_type":"tissue"},{"label":"paraspinal region","ontology_term_id":"UBERON:8480060","tissue_type":"tissue"},{"label":"thoracic segment connective tissue","ontology_term_id":"UBERON:0003837","tissue_type":"tissue"}]}],"description":"Our dataset contains single-cell and single-nuclei data for two cohorts for children with rhabdomyosarcoma (RMS) and other sarcomas, as well as single-cell data for two fusion-negative tumouroid models that were induced with the PAX3:FOXO1 fusion. For our first cohort, we sequenced 23 tumours (19 RMS and 4 Ewings), including 4 FP-ARMS, 1 FN-ARMS, and 13 FN-ERMS (2 harbouring MYOD1 mutations). In our second \u201cextension cohort\u201d we applied single-nuclei sequencing to 26 RMS, 2 Osteosarcoma, 1 Desmoplastic small round cell and 1 isolated Myofibroma tumour. Not all samples contained malignant cells. Finally, we applied single-cell sequencing to two fusion-negative RMS tumouroid models (RMS000OYW  & RMS444) - both control and with PAX3:FOXO1 overexpression.","doi":null,"is_pre_analysis":false,"links":[],"name":"A convergent cell state of lethal disease in rhabdomyosarcoma","published_at":"2026-07-10T16:05:53+00:00","publisher_metadata":null,"revised_at":null,"revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2902f08c-f83c-470e-a541-e463e25e5058","collection_url":"https://cellxgene.cziscience.com/collections/2902f08c-f83c-470e-a541-e463e25e5058","collection_version_id":"8c633adc-7cd1-4ace-8d87-ff7d332aa837","consortia":[],"contact_email":"lopes@lumc.nl","contact_name":"S. M. Chuva de Sousa Lopes","created_at":"2026-06-10T01:06:27+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"1f1c5c14-5949-4c81-b28e-b272e271b672","dataset_version_id":"e9f382d7-074c-4e10-97ba-47cf838cdf94","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]}],"description":"The ovary is perhaps the most dynamic organ in the human body, only rivaled by the uterus. The molecular mechanisms that regulate follicular growth and regression, ensuring ovarian tissue homeostasis, remain elusive. We have performed single-cell RNA-sequencing using human adult ovaries to provide a map of the molecular signature of growing and regressing follicular populations. We have identified different types of granulosa and theca cells and detected local production of components of the complement system by (atretic) theca cells and stromal cells. We also have detected a mixture of adaptive and innate immune cells, as well as several types of endothelial and smooth muscle cells to aid the remodeling process. Our results highlight the relevance of mapping whole adult organs at the single-cell level and reflect ongoing efforts to map the human body. The association between complement system and follicular remodeling may provide key insights in reproductive biology and (in)fertility.","doi":"10.1038/s41467-019-11036-9","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=ovarian-follicle-recon"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/faeedcb0-e046-4be7-b1ad-80a3eeabb066"},{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/johnmous/singleCell"},{"link_name":"GSE118127","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118127"}],"name":"Single-cell reconstruction of follicular remodeling in the human adult ovary","published_at":"2022-06-20T09:32:24+00:00","publisher_metadata":{"authors":[{"family":"Fan","given":"X."},{"family":"Bialecka","given":"M."},{"family":"Moustakas","given":"I."},{"family":"Lam","given":"E."},{"family":"Torrens-Juaneda","given":"V."},{"family":"Borggreven","given":"N. V."},{"family":"Trouw","given":"L."},{"family":"Louwe","given":"L. A."},{"family":"Pilgram","given":"G. S. K."},{"family":"Mei","given":"H."},{"family":"van der Westerlaken","given":"L."},{"family":"Chuva de Sousa Lopes","given":"S. M."}],"is_preprint":false,"journal":"Nat Commun","published_at":1575158400.0,"published_day":1,"published_month":12,"published_year":2019},"revised_at":"2026-06-11T16:53:54+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ecb739c5-fe0d-4b48-81c6-217c4d64eec4","collection_url":"https://cellxgene.cziscience.com/collections/ecb739c5-fe0d-4b48-81c6-217c4d64eec4","collection_version_id":"2d371dd8-a60a-4193-8fe4-05753e440ce6","consortia":[],"contact_email":"Sergei.Koralov@nyulangone.org","contact_name":"Sergei Koralov","created_at":"2026-06-10T01:10:46+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"bc260987-8ee5-4b6e-8773-72805166b3f7","dataset_version_id":"f033bbae-a7d8-43a7-9b1b-14a4c47a824c","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"693ae928-96ba-47de-b9d9-1321c675bfcd","dataset_version_id":"f26409bb-d367-4e90-bb5e-493334a1bc59","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"242c6e7f-9016-4048-af70-d631f5eea188","dataset_version_id":"25a21458-fa51-4fd0-8b2f-b044c557c053","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"1a7e99fe-d5b6-44d7-aa50-c6ef6ab29761","dataset_version_id":"b2efd134-d5dd-4e02-9335-eddd35d563fa","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"1a434263-2aa5-4fd9-a1f3-1c4a2a8fb771","dataset_version_id":"efe850f7-217a-4375-bf55-1820eccfe46c","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Both SARS-CoV-2 infection and vaccination elicit potent immune responses, but the durability and scope of immune responses remain to be elucidated. Here, we performed multimodal single- cell profiling of peripheral blood of patients with acute COVID-19 and healthy volunteers before and after receiving the SARS-CoV-2 BNT162b2 mRNA vaccine and booster, and compared the immune responses elicited by the virus and by the vaccine. Phenotypic and transcriptional profiling of immune cells, coupled with reconstruction of B cell and T cell receptor repertoires, enabled us to compare the host responses to the virus and to defined viral antigens. In COVID-19 patients, immune responses were characterized by a highly augmented interferon signature which was largely absent in vaccine recipients. We also observed a striking upregulation of cytotoxic genes in the peripheral T cells and innate-like lymphocytes in COVID-19 patients that was absent among healthy vaccinated individuals. These observations, were readily validated in an independent single-cell sequencing dataset. Analysis of B and T cell repertoires revealed that while the majority of clonal lymphocytes in COVID-19 patients were effector cells, in vaccine recipients clonal expansion was more evident among circulating memory cells. Furthermore, while clonal \u03b1\u03b2 T cell responses were observed in both COVID-19 patients and vaccine recipients, dramatic expansion of circulating clonal gdT cells was found only infected individuals. Overall, our analysis of immune responses to infection and to the mRNA vaccine revealed that while differences exist in response to infection compared to response to defined antigen, the vaccine elicits a robust adaptive immune response in the absence of severe inflammation associated with infection with notable increase in clonal B and T cell memory responses.","doi":"10.1016/j.isci.2023.108572","is_pre_analysis":false,"links":[{"link_name":"GSE247917","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE247917"}],"name":"COVID-19 mRNA vaccine elicits a potent adaptive immune response in the absence of persistent inflammation observed in SARS-CoV-2 infection","published_at":"2023-12-04T22:41:04+00:00","publisher_metadata":{"authors":[{"family":"Ivanova","given":"Ellie N."},{"family":"Shwetar","given":"Jasmine"},{"family":"Devlin","given":"Joseph C."},{"family":"Buus","given":"Terkild B."},{"family":"Gray-Gaillard","given":"Sophie"},{"family":"Koide","given":"Akiko"},{"family":"Cornelius","given":"Amber"},{"family":"Samanovic","given":"Marie I."},{"family":"Herrera","given":"Alberto"},{"family":"Mimitou","given":"Eleni P."},{"family":"Zhang","given":"Chenzhen"},{"family":"Karmacharya","given":"Trishala"},{"family":"Desvignes","given":"Ludovic"},{"family":"\u00d8dum","given":"Niels"},{"family":"Smibert","given":"Peter"},{"family":"Ulrich","given":"Robert J."},{"family":"Mulligan","given":"Mark J."},{"family":"Koide","given":"Shohei"},{"family":"Ruggles","given":"Kelly V."},{"family":"Herati","given":"Ramin S."},{"family":"Koralov","given":"Sergei B."}],"is_preprint":false,"journal":"iScience","published_at":1701388800.0,"published_day":1,"published_month":12,"published_year":2023},"revised_at":"2026-06-11T16:53:55+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"328d71f0-0ed7-4518-966f-be6bd0797324","collection_url":"https://cellxgene.cziscience.com/collections/328d71f0-0ed7-4518-966f-be6bd0797324","collection_version_id":"ca6735ab-e21f-4f51-a61f-07f57747e2b5","consortia":["CZI Cell Science"],"contact_email":"nhuebner@mdc-berlin.de","contact_name":"Norbert H\u00fcbner","created_at":"2026-06-10T07:17:23+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' 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v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"02474d5c-7faa-4567-80f8-56abc0a1df62","dataset_version_id":"3056e501-1f69-4cd6-bc1e-af6ee7ec4c5e","disease":[{"label":"myocarditis","ontology_term_id":"MONDO:0004496"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"}]}],"description":"Myocarditis, characterized by inflammatory cell infiltration, can have multiple etiologies, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or, rarely, mRNA-based coronavirus disease 2019 (COVID-19) vaccination. The underlying cellular and molecular mechanisms remain poorly understood. In this study, we performed single-nucleus RNA sequencing on left ventricular endomyocardial biopsies from patients with myocarditis unrelated to COVID-19 (Non-COVID-19), after SARS-CoV-2 infection (Post-COVID-19) and after COVID-19 vaccination (Post-Vaccination). We identified distinct cytokine expression patterns, with interferon-\u03b3 playing a key role in Post-COVID-19, and upregulated IL16 and IL18 expression serving as a hallmark of Post-Vaccination myocarditis. Although myeloid responses were similar across all groups, the Post-Vaccination group showed a higher proportion of CD4+ T cells, and the Post-COVID-19 group exhibited an expansion of cytotoxic CD8+ T and natural killer cells. Endothelial cells showed gene expression changes indicative of vascular barrier dysfunction in the Post-COVID-19 group and ongoing angiogenesis across all groups. These findings highlight shared and distinct mechanisms driving myocarditis in patients with and without a history of SARS-CoV-2 infection or vaccination.","doi":"10.1038/s44161-025-00612-6","is_pre_analysis":false,"links":[{"link_name":"EGAS50000000769","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS50000000769"},{"link_name":"PRJEB39602","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB39602"},{"link_name":"EGAD00001009292","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001009292"},{"link_name":"Reichart et al. (2022) Science","link_type":"OTHER","link_url":"https://doi.org/10.1126/science.abo1984"},{"link_name":"Litvi\u0148ukov\u00e1 et al. (2020) Nature","link_type":"OTHER","link_url":"https://doi.org/10.1038/s41586-020-2797-4"}],"name":"The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination","published_at":"2025-05-06T17:41:05+00:00","publisher_metadata":{"authors":[{"family":"Maatz","given":"Henrike"},{"family":"Lindberg","given":"Eric L."},{"family":"Adami","given":"Eleonora"},{"family":"L\u00f3pez-Anguita","given":"Natalia"},{"family":"Perdomo-Sabogal","given":"Alvaro"},{"family":"Cocera Ortega","given":"Luc\u00eda"},{"family":"Patone","given":"Giannino"},{"family":"Reichart","given":"Daniel"},{"family":"Myronova","given":"Anna"},{"family":"Schmidt","given":"Sabine"},{"family":"Elsanhoury","given":"Ahmed"},{"family":"Klein","given":"Oliver"},{"family":"K\u00fchl","given":"Uwe"},{"family":"Wyler","given":"Emanuel"},{"family":"Landthaler","given":"Markus"},{"family":"Yousefian","given":"Schayan"},{"family":"Haas","given":"Simon"},{"family":"Kurth","given":"Florian"},{"family":"Teichmann","given":"Sarah A."},{"family":"Oudit","given":"Gavin Y."},{"family":"Milting","given":"Hendrik"},{"family":"Noseda","given":"Michela"},{"family":"Seidman","given":"Jonathan G."},{"family":"Seidman","given":"Christine E."},{"family":"Heidecker","given":"Bettina"},{"family":"Sander","given":"Leif E."},{"family":"Sawitzki","given":"Birgit"},{"family":"Klingel","given":"Karin"},{"family":"Doeblin","given":"Patrick"},{"family":"Kelle","given":"Sebastian"},{"family":"Van Linthout","given":"Sophie"},{"family":"Hubner","given":"Norbert"},{"family":"Tsch\u00f6pe","given":"Carsten"}],"is_preprint":false,"journal":"Nat Cardiovasc Res","published_at":1740355200.0,"published_day":24,"published_month":2,"published_year":2025},"revised_at":"2026-06-11T16:53:55+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0a839c4b-10d0-4d64-9272-684c49a2c8ba","collection_url":"https://cellxgene.cziscience.com/collections/0a839c4b-10d0-4d64-9272-684c49a2c8ba","collection_version_id":"40ed6e8b-1dd9-4c0f-be51-6e518653d1db","consortia":[],"contact_email":"zemin@pku.edu.cn","contact_name":"Zemin Zhang","created_at":"2026-06-10T12:03:25+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"9dbab10c-118d-496b-966a-67f1763a6b7d","dataset_version_id":"481a2da9-2e61-424a-87e4-171e940006a4","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"},{"label":"saliva","ontology_term_id":"UBERON:0001836","tissue_type":"tissue"}]}],"description":"A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.","doi":"10.1016/j.cell.2021.01.053","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://data.mendeley.com/datasets/dvp4y5ttd5"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"http://covid19.cancer-pku.cn/"},{"link_name":"GSE158055","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE158055"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://cancer-pku.cn/"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-critical-immuno"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/5f607e50-ba22-4598-b1e9-f3d9d7a35dcc"},{"link_name":"HRA001149","link_type":"RAW_DATA","link_url":"https://ngdc.cncb.ac.cn/gsa-human/browse/HRA001149"}],"name":"COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas","published_at":"2021-04-09T00:22:37+00:00","publisher_metadata":{"authors":[{"family":"Ren","given":"Xianwen"},{"family":"Wen","given":"Wen"},{"family":"Fan","given":"Xiaoying"},{"family":"Hou","given":"Wenhong"},{"family":"Su","given":"Bin"},{"family":"Cai","given":"Pengfei"},{"family":"Li","given":"Jiesheng"},{"family":"Liu","given":"Yang"},{"family":"Tang","given":"Fei"},{"family":"Zhang","given":"Fan"},{"family":"Yang","given":"Yu"},{"family":"He","given":"Jiangping"},{"family":"Ma","given":"Wenji"},{"family":"He","given":"Jingjing"},{"family":"Wang","given":"Pingping"},{"family":"Cao","given":"Qiqi"},{"family":"Chen","given":"Fangjin"},{"family":"Chen","given":"Yuqing"},{"family":"Cheng","given":"Xuelian"},{"family":"Deng","given":"Guohong"},{"family":"Deng","given":"Xilong"},{"family":"Ding","given":"Wenyu"},{"family":"Feng","given":"Yingmei"},{"family":"Gan","given":"Rui"},{"family":"Guo","given":"Chuang"},{"family":"Guo","given":"Weiqiang"},{"family":"He","given":"Shuai"},{"family":"Jiang","given":"Chen"},{"family":"Liang","given":"Juanran"},{"family":"Li","given":"Yi-min"},{"family":"Lin","given":"Jun"},{"family":"Ling","given":"Yun"},{"family":"Liu","given":"Haofei"},{"family":"Liu","given":"Jianwei"},{"family":"Liu","given":"Nianping"},{"family":"Liu","given":"Shu-Qiang"},{"family":"Luo","given":"Meng"},{"family":"Ma","given":"Qiang"},{"family":"Song","given":"Qibing"},{"family":"Sun","given":"Wujianan"},{"family":"Wang","given":"GaoXiang"},{"family":"Wang","given":"Feng"},{"family":"Wang","given":"Ying"},{"family":"Wen","given":"Xiaofeng"},{"family":"Wu","given":"Qian"},{"family":"Xu","given":"Gang"},{"family":"Xie","given":"Xiaowei"},{"family":"Xiong","given":"Xinxin"},{"family":"Xing","given":"Xudong"},{"family":"Xu","given":"Hao"},{"family":"Yin","given":"Chonghai"},{"family":"Yu","given":"Dongdong"},{"family":"Yu","given":"Kezhuo"},{"family":"Yuan","given":"Jin"},{"family":"Zhang","given":"Biao"},{"family":"Zhang","given":"Peipei"},{"family":"Zhang","given":"Tong"},{"family":"Zhao","given":"Jincun"},{"family":"Zhao","given":"Peidong"},{"family":"Zhou","given":"Jianfeng"},{"family":"Zhou","given":"Wei"},{"family":"Zhong","given":"Sujuan"},{"family":"Zhong","given":"Xiaosong"},{"family":"Zhang","given":"Shuye"},{"family":"Zhu","given":"Lin"},{"family":"Zhu","given":"Ping"},{"family":"Zou","given":"Bin"},{"family":"Zou","given":"Jiahua"},{"family":"Zuo","given":"Zengtao"},{"family":"Bai","given":"Fan"},{"family":"Huang","given":"Xi"},{"family":"Zhou","given":"Penghui"},{"family":"Jiang","given":"Qinghua"},{"family":"Huang","given":"Zhiwei"},{"family":"Bei","given":"Jin-Xin"},{"family":"Wei","given":"Lai"},{"family":"Bian","given":"Xiu-Wu"},{"family":"Liu","given":"Xindong"},{"family":"Cheng","given":"Tao"},{"family":"Li","given":"Xiangpan"},{"family":"Zhao","given":"Pingsen"},{"family":"Wang","given":"Fu-Sheng"},{"family":"Wang","given":"Hongyang"},{"family":"Su","given":"Bing"},{"family":"Zhang","given":"Zheng"},{"family":"Qu","given":"Kun"},{"family":"Wang","given":"Xiaoqun"},{"family":"Chen","given":"Jiekai"},{"family":"Jin","given":"Ronghua"},{"family":"Zhang","given":"Zemin"}],"is_preprint":false,"journal":"Cell","published_at":1617235200.0,"published_day":1,"published_month":4,"published_year":2021},"revised_at":"2026-06-11T16:54:00+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"793fdaec-5067-428a-a9db-ecefe135c945","collection_url":"https://cellxgene.cziscience.com/collections/793fdaec-5067-428a-a9db-ecefe135c945","collection_version_id":"c0a2e274-944c-4221-b481-a9f7a4703c66","consortia":["Wellcome 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"1a2e3350-28a8-4f49-b33c-5b67ceb001f6","dataset_version_id":"47362a52-4a8c-48ae-8968-00d4e57d1dfc","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]}],"description":"Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11\u201312 weeks after conception, yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6\u20137 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21).","doi":"10.1038/s41586-021-03929-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://fbm.cellatlas.io/"},{"link_name":"Haniffa Lab","link_type":"LAB_WEBSITE","link_url":"https://haniffalab.com/"},{"link_name":"FBM Smart-seq2 scRNA-seq (E-MTAB-9801)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9801"},{"link_name":"Python and R code and notebooks for reproducing single-cell analyses","link_type":"OTHER","link_url":"https://github.com/haniffalab/FCA_bone_marrow"},{"link_name":"CD34+ FBM, fetal liver and cord blood CITE-seq (GSE166895)","link_type":"RAW_DATA","link_url":"http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE166895"},{"link_name":"FBM total CITE-seq (GSE166895)","link_type":"RAW_DATA","link_url":"http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE166895"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/04ad400c-58cb-40a5-bc2b-2279e13a910b"},{"link_name":"FBM from fetuses without Down syndrome (ERP125305)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB41514"},{"link_name":"FBM from fetuses with Down syndrome (E-MTAB-10042)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10042"},{"link_name":"FBM from fetuses with Down syndrome and FBM from fetuses without Down syndrome (E-MTAB-9389)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9389"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-CURD-112"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-MTAB-9801"}],"name":"Blood and immune development in human fetal bone marrow and Down syndrome","published_at":"2022-11-07T16:46:31+00:00","publisher_metadata":{"authors":[{"family":"Jardine","given":"Laura"},{"family":"Webb","given":"Simone"},{"family":"Goh","given":"Issac"},{"family":"Quiroga Londo\u00f1o","given":"Mariana"},{"family":"Reynolds","given":"Gary"},{"family":"Mather","given":"Michael"},{"family":"Olabi","given":"Bayanne"},{"family":"Stephenson","given":"Emily"},{"family":"Botting","given":"Rachel A."},{"family":"Horsfall","given":"Dave"},{"family":"Engelbert","given":"Justin"},{"family":"Maunder","given":"Daniel"},{"family":"Mende","given":"Nicole"},{"family":"Murnane","given":"Caitlin"},{"family":"Dann","given":"Emma"},{"family":"McGrath","given":"Jim"},{"family":"King","given":"Hamish"},{"family":"Kucinski","given":"Iwo"},{"family":"Queen","given":"Rachel"},{"family":"Carey","given":"Christopher D."},{"family":"Shrubsole","given":"Caroline"},{"family":"Poyner","given":"Elizabeth"},{"family":"Acres","given":"Meghan"},{"family":"Jones","given":"Claire"},{"family":"Ness","given":"Thomas"},{"family":"Coulthard","given":"Rowen"},{"family":"Elliott","given":"Natalina"},{"family":"O\u2019Byrne","given":"Sorcha"},{"family":"Haltalli","given":"Myriam L. R."},{"family":"Lawrence","given":"John E."},{"family":"Lisgo","given":"Steven"},{"family":"Balogh","given":"Petra"},{"family":"Meyer","given":"Kerstin B."},{"family":"Prigmore","given":"Elena"},{"family":"Ambridge","given":"Kirsty"},{"family":"Jain","given":"Mika Sarkin"},{"family":"Efremova","given":"Mirjana"},{"family":"Pickard","given":"Keir"},{"family":"Creasey","given":"Thomas"},{"family":"Bacardit","given":"Jaume"},{"family":"Henderson","given":"Deborah"},{"family":"Coxhead","given":"Jonathan"},{"family":"Filby","given":"Andrew"},{"family":"Hussain","given":"Rafiqul"},{"family":"Dixon","given":"David"},{"family":"McDonald","given":"David"},{"family":"Popescu","given":"Dorin-Mirel"},{"family":"Kowalczyk","given":"Monika S."},{"family":"Li","given":"Bo"},{"family":"Ashenberg","given":"Orr"},{"family":"Tabaka","given":"Marcin"},{"family":"Dionne","given":"Danielle"},{"family":"Tickle","given":"Timothy L."},{"family":"Slyper","given":"Michal"},{"family":"Rozenblatt-Rosen","given":"Orit"},{"family":"Regev","given":"Aviv"},{"family":"Behjati","given":"Sam"},{"family":"Laurenti","given":"Elisa"},{"family":"Wilson","given":"Nicola K."},{"family":"Roy","given":"Anindita"},{"family":"G\u00f6ttgens","given":"Berthold"},{"family":"Roberts","given":"Irene"},{"family":"Teichmann","given":"Sarah A."},{"family":"Haniffa","given":"Muzlifah"}],"is_preprint":false,"journal":"Nature","published_at":1634169600.0,"published_day":14,"published_month":10,"published_year":2021},"revised_at":"2026-06-11T16:53:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"059202e1-1f1b-483f-9151-f3a25a380c39","collection_url":"https://cellxgene.cziscience.com/collections/059202e1-1f1b-483f-9151-f3a25a380c39","collection_version_id":"f55a2aa4-dbb3-4934-95d9-50010f893260","consortia":["CZI Cell Science"],"contact_email":"gary.bader@utoronto.ca","contact_name":"Gary Bader","created_at":"2024-06-13T21:20:35+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"ef3055e1-0cad-40a3-961d-7110a323dc4f","dataset_version_id":"05955131-98d8-4be1-b419-efb690a4e258","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"4bf585ea-0d0d-483c-a3c9-36f44a5b1adf","dataset_version_id":"9c16200d-6087-4d8e-a211-413d4f991144","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"375f79e2-4ae4-4016-8e5e-8b15f8cc7a41","dataset_version_id":"ef880836-ca89-4258-8f86-1668c7415efa","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"2db80173-2bbb-499c-9161-dff672eb12e9","dataset_version_id":"1d29777b-80c4-44ed-a6b2-e5431c074c34","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"2a6eb5f1-8ccc-4781-9ac8-294e671243ef","dataset_version_id":"eb7c9548-e248-4dcf-ba1f-195531bde8c8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"199febfe-32c1-4cf7-9bd9-745206458d06","dataset_version_id":"ffeb8e55-1cfb-4371-9c10-e708fc23bb6f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"024f5d59-750b-4bf2-8937-51cd4b8b8e32","dataset_version_id":"50279847-aeeb-46c0-817d-45042ba8997e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]}],"description":"The human liver is composed of a heterogeneous mix of cell types. How these distinct\npopulations contribute individually and collectively to liver function remains poorly understood.\nAlthough single-cell technologies have advanced our understanding of liver biology, individual\nstudies have often been limited by small donor cohorts and inconsistent cell type annotations.\nIntegrating multiple datasets can overcome these challenges and better capture biological\nvariability.\nWe present the Human Liver Cell Atlas (HLiCA), an integrated reference of non-disease liver\ncells assembled from eight datasets across six research centers, encompassing more than\n525,000 cells from 110 donors. Developed in collaboration with the Human Cell Atlas Liver\nBionetwork, the HLiCA incorporates expert-curated cell annotations refined through community\nfeedback and dedicated cell type annotation meetings. The HLiCA classifies cells into six\nlineages and expands the cell type resolution to include 47 distinct cell types. Starting from raw\nsequencing reads, we realigned all data and performed rigorous benchmarking to ensure robust\nintegration across technical and biological variables. Genetic ancestry was inferred for all\nsamples to evaluate the range of ancestral backgrounds represented in the atlas.\nThe expanded cell type annotation enabled identification of previously unrecognized liver\ncell types, including NRXN1+ stromal cells. Their presence was validated using spatial\ntranscriptomics, which localized NRXN1+ stromal cells to periportal regions. With the number of\ndonors included in the HLiCA we were able to examine cell type specific associations with\ndemographic covariates. In hepatocytes, drug metabolism genes showed differential expression\nbetween sexes, and in cholangiocytes, mucus-production genes varied with age.\nAs the largest and most genetically diverse human liver cell atlas to date, the HLiCA\nprovides a comprehensive, well-annotated reference for the field, annotated by expert\nconsensus. This resource will enable deeper interrogation of liver cellular diversity, architecture,\nand function in the healthy human liver and serve as a reference to understand changes that\noccur with disease.","doi":"10.64898/2026.06.30.735539","is_pre_analysis":false,"links":[],"name":"HLiCA: An integrated cell atlas of the healthy human liver","published_at":"2026-07-20T19:00:32+00:00","publisher_metadata":{"authors":[{"family":"Edgar","given":"Rachel D."},{"family":"Portman","given":"Jordan R."},{"family":"Hu","given":"Hongru"},{"family":"Pouyabahar","given":"Delaram"},{"family":"Rahman","given":"Raza R."},{"family":"Stueckmann","given":"Daniel"},{"family":"Choi","given":"Yongin"},{"family":"Neavin","given":"Drew R."},{"family":"Atif","given":"Jawairia"},{"family":"Clarke","given":"Zoe A."},{"family":"Gao","given":"Ran"},{"family":"Khare","given":"Shruti"},{"family":"Li","given":"Ziyi"},{"family":"Martens","given":"Liesbet"},{"family":"Murti","given":"Abhishek"},{"family":"Nakib","given":"Diana"},{"family":"Shirgaonkar","given":"Niranjan"},{"family":"Thomann","given":"Stefan"},{"family":"Thon\u00e9","given":"Tinne"},{"family":"Wilson-Kanamori","given":"John R."},{"family":"Breitkopf-Heinlein","given":"Katja"},{"family":"Lattouf","given":"Elias Isaac"},{"family":"Li","given":"Ruoxin"},{"family":"Napoliello","given":"Renee"},{"family":"Rahbari","given":"Nuh N."},{"family":"Sadria","given":"Mehrshad"},{"family":"Yakubovsky","given":"Oran"},{"family":"Andrews","given":"Tallulah"},{"family":"Aronow","given":"Bruce J."},{"family":"Cuenca","given":"Alex G."},{"family":"DePasquale","given":"Erica A.K."},{"family":"Huppert","given":"Stacey S."},{"family":"Itzkovitz","given":"Shalev"},{"family":"Lauer","given":"Georg M."},{"family":"Mysore","given":"Krupa R."},{"family":"Powell","given":"Joseph E."},{"family":"Schwartz","given":"Robert E."},{"family":"Sharma","given":"Ankur"},{"family":"Taylor","given":"Sarah A."},{"family":"Vallier","given":"Ludovic"},{"family":"Wang","given":"Bruce"},{"family":"Dasgupta","given":"Ramanuj"},{"family":"Gr\u00fcn","given":"Dominic"},{"family":"Guilliams","given":"Martin"},{"family":"Henderson","given":"Neil C."},{"family":"MacParland","given":"Sonya A."},{"family":"Scott","given":"Charlotte L."},{"family":"Mullen","given":"Alan"},{"family":"Quon","given":"Gerald"},{"family":"Bader","given":"Gary D."}],"is_preprint":true,"journal":"bioRxiv","published_at":1783123200.0,"published_day":4,"published_month":7,"published_year":2026},"revised_at":null,"revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bd5230f4-cd76-4d35-9ee5-89b3e7475659","collection_url":"https://cellxgene.cziscience.com/collections/bd5230f4-cd76-4d35-9ee5-89b3e7475659","collection_version_id":"a2107226-1b82-48f7-b896-49750f675cfa","consortia":[],"contact_email":"s.macparland@utoronto.ca","contact_name":"Sonya MacParland","created_at":"2026-07-18T00:05:05+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"a43aa46b-bd16-47fe-bc3e-19a052624e79","dataset_version_id":"9681a962-f2d0-4d53-8127-7ac87f2bd799","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]}],"description":"The liver is the largest solid organ in the body and is critical for metabolic and immune functions. However, little is known about the cells that make up the human liver and its immune microenvironment. Here we report a map of the cellular landscape of the human liver using single-cell RNA sequencing. We provide the transcriptional profiles of 8444 parenchymal and non-parenchymal cells obtained from the fractionation of fresh hepatic tissue from five human livers. Using gene expression patterns, flow cytometry, and immunohistochemical examinations, we identify 20 discrete cell populations of hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, B cells, conventional and non-conventional T cells, NK-like cells, and distinct intrahepatic monocyte/macrophage populations. Together, our study presents a comprehensive view of the human liver at single-cell resolution that outlines the characteristics of resident cells in the liver, and in particular provides a map of the human hepatic immune microenvironment.","doi":"10.1038/s41467-018-06318-7","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/4d6f6c96-2a83-43d8-8fe1-0f53bffd4674"},{"link_name":"Bader Lab","link_type":"LAB_WEBSITE","link_url":"http://www.baderlab.org/"},{"link_name":"GSE115469","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115469"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-HCAD-9"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=human-liver"}],"name":"Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations","published_at":"2022-10-10T15:18:12+00:00","publisher_metadata":{"authors":[{"family":"MacParland","given":"Sonya A."},{"family":"Liu","given":"Jeff C."},{"family":"Ma","given":"Xue-Zhong"},{"family":"Innes","given":"Brendan T."},{"family":"Bartczak","given":"Agata M."},{"family":"Gage","given":"Blair K."},{"family":"Manuel","given":"Justin"},{"family":"Khuu","given":"Nicholas"},{"family":"Echeverri","given":"Juan"},{"family":"Linares","given":"Ivan"},{"family":"Gupta","given":"Rahul"},{"family":"Cheng","given":"Michael L."},{"family":"Liu","given":"Lewis Y."},{"family":"Camat","given":"Damra"},{"family":"Chung","given":"Sai W."},{"family":"Seliga","given":"Rebecca K."},{"family":"Shao","given":"Zigong"},{"family":"Lee","given":"Elizabeth"},{"family":"Ogawa","given":"Shinichiro"},{"family":"Ogawa","given":"Mina"},{"family":"Wilson","given":"Michael D."},{"family":"Fish","given":"Jason E."},{"family":"Selzner","given":"Markus"},{"family":"Ghanekar","given":"Anand"},{"family":"Grant","given":"David"},{"family":"Greig","given":"Paul"},{"family":"Sapisochin","given":"Gonzalo"},{"family":"Selzner","given":"Nazia"},{"family":"Winegarden","given":"Neil"},{"family":"Adeyi","given":"Oyedele"},{"family":"Keller","given":"Gordon"},{"family":"Bader","given":"Gary D."},{"family":"McGilvray","given":"Ian D."}],"is_preprint":false,"journal":"Nat Commun","published_at":1543622400.0,"published_day":1,"published_month":12,"published_year":2018},"revised_at":"2026-07-20T21:51:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"847fafc3-41a1-4a0d-9461-0328c88e9b13","collection_url":"https://cellxgene.cziscience.com/collections/847fafc3-41a1-4a0d-9461-0328c88e9b13","collection_version_id":"eee36a6b-2976-4f7a-9955-95c869be26ca","consortia":[],"contact_email":"james.briscoe@crick.ac.uk","contact_name":"James Briscoe","created_at":"2026-06-10T03:02:34+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"b62f728b-a7eb-4889-8162-b3d457de93b9","dataset_version_id":"78c6096a-bcc3-45e4-91f8-2eb350dd1f54","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"neural tube","ontology_term_id":"UBERON:0001049","tissue_type":"tissue"}]}],"description":"The spinal cord receives input from peripheral sensory neurons and controls motor output by regulating muscle innervating motor neurons. These functions are carried out by neural circuits comprising molecularly distinct neuronal subtypes generated in a characteristic spatiotemporal arrangement from progenitors in the embryonic neural tube. To gain insight into the diversity and complexity of cells in the developing human neural tube, we used single-cell mRNA sequencing to profile cervical and thoracic regions in four human embryos of Carnegie stages (CS) CS12, CS14, CS17 and CS19 from gestational weeks 4-7. Analysis of progenitor and neuronal populations from the neural tube and dorsal root ganglia identified dozens of distinct cell types and facilitated the reconstruction of the differentiation pathways of specific neuronal subtypes. Comparison with mouse revealed overall similarity of mammalian neural tube development while highlighting some human-specific features. These data provide a catalogue of gene expression and cell type identity in the human neural tube that will support future studies of sensory and motor control systems.","doi":"10.1242/dev.199711","is_pre_analysis":false,"links":[{"link_name":"GSE171892","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE171892"}],"name":"Single-cell transcriptome profiling of the human developing spinal cord reveals a conserved genetic programme with human-specific features","published_at":"2024-03-28T18:13:16+00:00","publisher_metadata":{"authors":[{"family":"Rayon","given":"Teresa"},{"family":"Maizels","given":"Rory J."},{"family":"Barrington","given":"Christopher"},{"family":"Briscoe","given":"James"}],"is_preprint":false,"journal":"Development","published_at":1627776000.0,"published_day":1,"published_month":8,"published_year":2021},"revised_at":"2026-06-11T16:54:00+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ceef2841-5333-46ac-92ef-ccbe0c20fe55","collection_url":"https://cellxgene.cziscience.com/collections/ceef2841-5333-46ac-92ef-ccbe0c20fe55","collection_version_id":"cb6e09da-7718-42fc-97ac-c439524999ae","consortia":[],"contact_email":"mmrao@mdanderson.org","contact_name":"Mitchell Rao","created_at":"2026-06-10T02:54:39+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"6f9de485-58cd-4342-bfc4-b3d3dd223aa8","dataset_version_id":"e94bd3cc-6271-424a-baac-12f8eb320a0e","disease":[{"label":"triple-negative breast carcinoma","ontology_term_id":"MONDO:0005494"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"}]}],"description":"Single-cell RNA-seq were performed on the untreated samples of the treatment-naive triple negative breast cancer patients.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://github.com/navinlabcode/tnbc-chemo"}],"name":"Single-cell atlas of untreated human triple negative breast cancer","published_at":"2026-03-10T20:12:26+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:54:00+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"79403b27-5330-43d6-b136-bf3976dd94b8","collection_url":"https://cellxgene.cziscience.com/collections/79403b27-5330-43d6-b136-bf3976dd94b8","collection_version_id":"3abffa24-7227-4263-84a5-4e84da4748db","consortia":[],"contact_email":"ambre.baillou@unibe.ch","contact_name":"Ambre BAILLOU","created_at":"2026-06-10T05:59:52+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0b9fc518-7ee8-43ec-bfb0-f65c0af0ae82","dataset_version_id":"8ec087b0-5c3f-4dab-9de6-92cb6e5fa468","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Sus scrofa","ontology_term_id":"NCBITaxon:9823"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Dendritic cells (DC) are professional antigen presenting cells playing a major role in orchestrating adaptative immune responses. To adapt to various immune challenges, such as different classes of pathogens, specialized subsets of DC have evolved across species. To date, DC are classified as conventional DC (cDC1, cDC2) and plasmacytoid DC (pDC), with the more recent addition of DC3 and transitional DC (tDC) that were discovered in human and mouse thanks to high-dimensional phenotyping and single-cell sequencing technologies. Here, by combining flow cytometry and RNA-seq on the bulk- and single-cell level, we identified the porcine equivalent of tDC in blood as CD14- CADM1- CD172a+ CD4- cells expressing both Flt3 and CD123 (IL-3RA). This new subset forms a well-defined cluster when mapped onto scRNA-seq data of enriched DC and shares transcriptomic features and abundance with porcine blood cDC2 and pDC. Moreover, we describe putative porcine DC3 as transcriptionally overlapping cells in-between cDC2 and monocytes. With the core functions of tDC and DC3 remaining to be elucidated, our datasets provide a valuable resource for cross-species research on DC heterogeneity in various lymphoid and non-lymphoid tissues.","doi":"10.3389/fimmu.2025.1639553","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB101131"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/IVI-Immunology/Porcine_blood_DC_scRNA-seq"}],"name":"Unraveling porcine dendritic-cell diversity: welcome tDC and DC3","published_at":"2026-03-12T17:18:11+00:00","publisher_metadata":{"authors":[{"family":"Baillou","given":"Ambre"},{"family":"Auray","given":"Ga\u00ebl"},{"family":"Brito","given":"Francisco"},{"family":"Botos","given":"Marius"},{"family":"Huber","given":"Aliz\u00e9e"},{"family":"Summerfield","given":"Artur"},{"family":"Talker","given":"Stephanie C."}],"is_preprint":false,"journal":"Front. Immunol.","published_at":1761696000.0,"published_day":29,"published_month":10,"published_year":2025},"revised_at":"2026-06-11T16:53:05+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e4c9ed14-e560-4900-a3bf-b0f8d2ce6a10","collection_url":"https://cellxgene.cziscience.com/collections/e4c9ed14-e560-4900-a3bf-b0f8d2ce6a10","collection_version_id":"704c3bfe-ec3b-413e-8a01-b3e3291dd32a","consortia":[],"contact_email":"jq2240@cumc.columbia.edu","contact_name":"Jianwen Que","created_at":"2026-06-10T18:33:28+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d8da613f-e681-4c69-b463-e94f5e66847f","dataset_version_id":"1792df55-7cfe-4564-afcf-4bb3ffb73bc0","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"Understanding cellular drivers of lethal SARS-CoV-2 infection is an essential first step towards improving therapies for severe COVID-19. We performed single-nuclei RNA-seq (snRNA-seq) on >116,000 nuclei from 19 COVID-19 autopsy lungs and seven pre-pandemic controls. Lungs from COVID-19 decedents show distinct fractional and (dys)functional changes across the immune and non-immune cellular landscape. This data set provides a rich single-cell landscape of lethal COVID-19 and initial insights into the cellular interplay that shapes the highly inflamed and remodeled lung ecosystem. The lung atlas presented here is the first in a series of data releases covering different organs profiled from COVID-19 patients.","doi":"10.1038/s41586-021-03569-1","is_pre_analysis":false,"links":[{"link_name":"SCP","link_type":"DATA_SOURCE","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1219/columbia-university-nyp-covid-19-lung-atlas#"},{"link_name":"GSE171524","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE171524"},{"link_name":"Human Cell Atlas","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/d7845650-f6b1-4b1c-b2fe-c0795416ba7b"},{"link_name":"UCSC Cell Browser","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-cellular-targets"}],"name":"A molecular single-cell lung atlas of lethal COVID-19","published_at":"2023-03-31T22:56:30+00:00","publisher_metadata":{"authors":[{"family":"Melms","given":"Johannes C."},{"family":"Biermann","given":"Jana"},{"family":"Huang","given":"Huachao"},{"family":"Wang","given":"Yiping"},{"family":"Nair","given":"Ajay"},{"family":"Tagore","given":"Somnath"},{"family":"Katsyv","given":"Igor"},{"family":"Rendeiro","given":"Andr\u00e9 F."},{"family":"Amin","given":"Amit Dipak"},{"family":"Schapiro","given":"Denis"},{"family":"Frangieh","given":"Chris J."},{"family":"Luoma","given":"Adrienne M."},{"family":"Filliol","given":"Aveline"},{"family":"Fang","given":"Yinshan"},{"family":"Ravichandran","given":"Hiranmayi"},{"family":"Clausi","given":"Mariano G."},{"family":"Alba","given":"George A."},{"family":"Rogava","given":"Meri"},{"family":"Chen","given":"Sean W."},{"family":"Ho","given":"Patricia"},{"family":"Montoro","given":"Daniel T."},{"family":"Kornberg","given":"Adam E."},{"family":"Han","given":"Arnold S."},{"family":"Bakhoum","given":"Mathieu 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E."},{"family":"Elemento","given":"Olivier"},{"family":"Saqi","given":"Anjali"},{"family":"Hibshoosh","given":"Hanina"},{"family":"Que","given":"Jianwen"},{"family":"Izar","given":"Benjamin"}],"is_preprint":false,"journal":"Nature","published_at":1625097600.0,"published_day":1,"published_month":7,"published_year":2021},"revised_at":"2026-06-11T16:52:33+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2f75d249-1bec-459b-bf2b-b86221097ced","collection_url":"https://cellxgene.cziscience.com/collections/2f75d249-1bec-459b-bf2b-b86221097ced","collection_version_id":"f77181c9-f72a-4c68-9afc-efdd18e8d3a4","consortia":["CZ Biohub","Human BioMolecular Atlas Program (HuBMAP)"],"contact_email":"rsatija@nygenome.org","contact_name":"Rahul Satija","created_at":"2026-06-10T00:58:35+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' 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harmonized annotation and visualization.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/4895404#.YYV4XkbML0o"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/satijalab/azimuth-references/tree/master/human_lung"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://satijalab.org/"},{"link_name":"Azimuth","link_type":"OTHER","link_url":"https://azimuth.hubmapconsortium.org/"}],"name":"Azimuth meta-analysis of human scRNA-seq datasets","published_at":"2021-05-14T16:54:19+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:54:01+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"283d65eb-dd53-496d-adb7-7570c7caa443","collection_url":"https://cellxgene.cziscience.com/collections/283d65eb-dd53-496d-adb7-7570c7caa443","collection_version_id":"bf0ef473-74a5-4956-bd4d-2fa19bd6c33b","consortia":["BRAIN Initiative","CZI Cell 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This broad range of functions is supported by an exceptionally complex cellular and circuit architecture.  To create a first draft human brain cell atlas, high-throughput single-nucleus RNA sequencing was used to systematically survey cells across the entire adult human brain in three postmortem donors. Over three million nuclei were sampled from approximately 100 dissections across the forebrain, midbrain, and hindbrain. Analysis of these data showed regional diversity in that cellular organization exhibited regional diversity at multiple scales, identifying 30 superclusters, 461 clusters and 3313 subclusters.  As the first single-cell transcriptomic census of the entire human brain, this atlas provides a resource for understanding the molecular diversity of the human brain in health and disease. The Human Brain Cell Atlas v1.0 is presented for visualization and data mining through the Chan Zuckerberg Initiative\u2019s CellxGene application, with the following biologically meaningful partitions: 1. Neuronal and non-neuronal cell types 2. Supercluster-specific groupings (\u201dSupercluster: \u201d) 3.Brain region-specific groupings (\u201dDissection: \u201c), ordered by the adult human brain anatomical reference atlas ontology in Ding et al. (2016)","doi":"10.1126/science.add7046","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"http://data.nemoarchive.org/biccn/grant/u01_lein/linnarsson/transcriptome/sncell/10x_v3/human/raw/"},{"link_name":"github (analysis and figures)","link_type":"OTHER","link_url":"https://github.com/linnarsson-lab/adult-human-brain"},{"link_name":"github (auto-annotations)","link_type":"OTHER","link_url":"https://github.com/linnarsson-lab/auto-annotation-ah"}],"name":"Human Brain Cell Atlas v1.0","published_at":"2022-12-09T18:17:51+00:00","publisher_metadata":{"authors":[{"family":"Siletti","given":"Kimberly"},{"family":"Hodge","given":"Rebecca"},{"family":"Mossi Albiach","given":"Alejandro"},{"family":"Lee","given":"Ka Wai"},{"family":"Ding","given":"Song-Lin"},{"family":"Hu","given":"Lijuan"},{"family":"L\u00f6nnerberg","given":"Peter"},{"family":"Bakken","given":"Trygve"},{"family":"Casper","given":"Tamara"},{"family":"Clark","given":"Michael"},{"family":"Dee","given":"Nick"},{"family":"Gloe","given":"Jessica"},{"family":"Hirschstein","given":"Daniel"},{"family":"Shapovalova","given":"Nadiya V."},{"family":"Keene","given":"C. 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nuclei.","doi":"10.1126/science.adf0834","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-3ah9h9x"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/velmeshevlab/dev_hum_cortex"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/7245297"},{"link_name":"","link_type":"OTHER","link_url":"https://pre-postnatal-cortex.cells.ucsc.edu"}],"name":"Single-cell analysis of prenatal and postnatal human cortical development","published_at":"2023-09-19T19:14:34+00:00","publisher_metadata":{"authors":[{"family":"Velmeshev","given":"Dmitry"},{"family":"Perez","given":"Yonatan"},{"family":"Yan","given":"Zihan"},{"family":"Valencia","given":"Jonathan E."},{"family":"Castaneda-Castellanos","given":"David 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We then analyzed ligand and receptor interactions and identified the alveolar type 1 (AT1) epithelial cell as a hub of ligand expression. The cognate receptors for these ligands were restricted to subsets of developing mesenchymal cells. Mesenchymal progenitors are spatially and transcriptionally segregated into Acta2-, Pdgfrb-, or Wnt2-expressing subsets and are committed to generating distinct fibroblasts in the postnatal lung by embryonic day 15.5 (E15.5). We show with scRNA-seq and lineage tracing that the progenitors for the transient secondary crest myofibroblast (SCMF), which exists only during the early postnatal alveolarization period of lung development, are spatially and transcriptionally aligned with AT1 cell progenitors. In comparison with other alveolar fibroblasts, SCMFs exert significantly more traction force ex vivo, indicating that they are a functionally specialized lineage that can remodel the alveolus. To identify intercellular signaling pathways that regulate cell lineage identity, we examined the single-cell chromatin accessibility and pathway expression (SCAPE) of AT1s and SCMFs. We identified Foxa and Tead transcription factors as upstream regulators of several AT1-derived ligands, including Shh and Wnt ligands. Conversely, SCMFs exhibit open chromatin with predicted Gli1 and Tcf target genes, implicating Shh and Wnt pathways in their development and function. To test these pathways, we generated AT1 cell\u2013specific conditional deletions for Wnt-ligand secretion (Wls) and Shh. Conditional ablation of Shh from AT1 cells results in a loss of SCMF cells and subsequent alveolar simplification in the postnatal lung.","doi":"10.1126/science.abc3172","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE149563"}],"name":"LungMAP \u2014 The genomic, epigenomic and biophysical cues controlling the emergence of the gas exchange niche in the lung.","published_at":"2021-10-11T23:13:24+00:00","publisher_metadata":{"authors":[{"family":"Zepp","given":"Jarod A."},{"family":"Morley","given":"Michael P."},{"family":"Loebel","given":"Claudia"},{"family":"Kremp","given":"Madison M."},{"family":"Chaudhry","given":"Fatima N."},{"family":"Basil","given":"Maria C."},{"family":"Leach","given":"John P."},{"family":"Liberti","given":"Derek C."},{"family":"Niethamer","given":"Terren 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Diagnoses included are Alzheimer\u2019s disease (AD), Progressive supranuclear Palsy (PSP), behavioral variant Frontotemporal dementia with Pick\u2019s disease neuropathology (bvFTD) and unaffected controls.  Brain regions included are motor cortex (BA4), insular cortex, and visual cortex. 8-11 cases per diagnosis and brain region.  Data provided for visualization is post quality control filtering.","doi":"10.1016/j.cell.2024.08.019","is_pre_analysis":false,"links":[{"link_name":"Analysis Code RNAseq","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.12734742"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.synapse.org/Synapse:syn52074156/"}],"name":"Cross-dementia human brain snRNA-seq (Rexach et al 2024)","published_at":"2024-09-11T16:12:01+00:00","publisher_metadata":{"authors":[{"family":"Rexach","given":"Jessica 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We describe precision-cut human lymph node (LN) slices as a functioning, architecturally preserved, full-organ cross-sectional model system. Using single-cell transcriptomics and multiplexed imaging, we explore early inflammatory response to a potent, clinically relevant liposomal vaccine adjuvant containing a TLR4-agonist and QS-21 saponin. Both TLR4 and NLRP3 inflammasome activation are involved in the direct initiation of the inflammatory response to adjuvant by monocytes and macrophages (Mon./Mac.) with secretion of interleukin (IL)-1\u03b2, but not IL-18, dependent on TLR4 signaling. Innate lymphoid cells, including natural killer cells, are indirectly activated by Mon./Mac.-produced cytokines, signaling downstream to B cells via interferon-\u03b3 secretion. Resident LN stromal populations, primed both directly and indirectly by vaccine adjuvant, are instrumental in mediating inflammatory cell recruitment, particularly neutrophils.","doi":"10.1016/j.celrep.2025.115938","is_pre_analysis":false,"links":[{"link_name":"GSE294959","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE294959"}],"name":"LNCS: Atlas of healthy human lymph nodes with and without ex vivo adjuvant stimulation","published_at":"2025-07-08T19:11:16+00:00","publisher_metadata":{"authors":[{"family":"Fergusson","given":"Joannah R."},{"family":"Siu","given":"Jacqueline H.Y."},{"family":"Gupta","given":"Nitya"},{"family":"Jenkins","given":"Edward"},{"family":"Nee","given":"Eloise"},{"family":"Reinke","given":"S\u00f6ren"},{"family":"Str\u00f6bel","given":"Tamara"},{"family":"Bhalla","given":"Ananya"},{"family":"Kandage","given":"Shyami 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By transfer learning, we \u2018upgraded\u2019 our atlas reference (extended GBmap) with another ten datasets, including our own profiled GB tissues resulting in a collection of 26 studies, 240 patients, and more than 1.1 million cells.","doi":"10.1101/2022.08.27.505439","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/6962901#.YwzPKezMLDA"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ccruizm/GBmap"}],"name":"Harmonized single-cell landscape, intercellular crosstalk and tumor architecture of glioblastoma","published_at":"2022-08-29T21:50:26+00:00","publisher_metadata":{"authors":[{"family":"Ruiz-Moreno","given":"Cristian"},{"family":"Salas","given":"Sergio Marco"},{"family":"Samuelsson","given":"Erik"},{"family":"Brandner","given":"Sebastian"},{"family":"Kranendonk","given":"Mariette E.G."},{"family":"Nilsson","given":"Mats"},{"family":"Stunnenberg","given":"Hendrik G."}],"is_preprint":true,"journal":"bioRxiv","published_at":1661558400.0,"published_day":27,"published_month":8,"published_year":2022},"revised_at":"2026-06-11T16:54:03+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0bebef1a-4607-4584-9070-dacf89a0d635","collection_url":"https://cellxgene.cziscience.com/collections/0bebef1a-4607-4584-9070-dacf89a0d635","collection_version_id":"7fea794a-14cd-49e6-9268-39d691c3573a","consortia":[],"contact_email":"jusung.lee@dkfz-heidelberg.de","contact_name":"Jusung Lee","created_at":"2026-06-10T14:06:53+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"01ff5cf0-730f-4ddc-b1be-7b407211f544","dataset_version_id":"229e74ee-9b3e-4ab2-bddb-9eccbac85b48","disease":[{"label":"lung adenocarcinoma","ontology_term_id":"MONDO:0005061"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung parenchyma","ontology_term_id":"UBERON:0008946","tissue_type":"tissue"}]}],"description":"Single-cell RNA sequencing reveals distinct tumor microenvironmental features across histological subtypes of lung adenocarcinoma (18 patients, 4 subtypes)","doi":"10.1186/s40164-025-00740-6","is_pre_analysis":false,"links":[],"name":"Defining the cellular and molecular identities of histologic subtypes in lung adenocarcinoma","published_at":"2026-01-26T17:57:14+00:00","publisher_metadata":{"authors":[{"family":"Lee","given":"Jusung"},{"family":"Jeong","given":"Ji Yun"},{"family":"Hong","given":"Mi Jeong"},{"family":"Choi","given":"Yoon Ha"},{"family":"Kim","given":"Ju Young"},{"family":"Lee","given":"Jang Hyuck"},{"family":"Choi","given":"Jin Eun"},{"family":"Kim","given":"Moonsik"},{"family":"Do","given":"Young Woo"},{"family":"Lee","given":"Eung Bae"},{"family":"Choi","given":"Sun Ha"},{"family":"Yoo","given":"Seung Soo"},{"family":"Park","given":"Jae Yong"},{"family":"Kim","given":"Jong Kyoung"},{"family":"Lee","given":"Shin Yup"}],"is_preprint":false,"journal":"Exp Hematol Oncol","published_at":1769126400.0,"published_day":23,"published_month":1,"published_year":2026},"revised_at":"2026-06-11T16:52:33+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c11009b8-b113-4a99-9890-78b2f9df9d79","collection_url":"https://cellxgene.cziscience.com/collections/c11009b8-b113-4a99-9890-78b2f9df9d79","collection_version_id":"a4996baf-010b-4b4d-bde1-c04b0ed749a7","consortia":[],"contact_email":"kriukov.e@northeastern.edu","contact_name":"Emil Kriukov","created_at":"2026-06-10T18:46:40+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"aecc2743-4ff2-4b55-ac8c-a1ff76fc4bb4","dataset_version_id":"3fdf264b-40f6-4f5a-b433-bddba1bbebf4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"central retina","ontology_term_id":"UBERON:8000004","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"},{"label":"retina","ontology_term_id":"UBERON:0000966","tissue_type":"tissue"}]}],"description":"Tissue development is a complex spatiotemporal process with multiple interdependent components. Anatomical, histological, sequencing, and evolutional strategies can be used to profile and explain tissue development from different perspectives. The introduction of scRNAseq methods and the computational tools allows to deconvolute developmental heterogeneity and draw a decomposed uniform map. In this manuscript, we decomposed the development of a human retina with a focus on the retinal ganglion cells (RGC). To increase the temporal resolution of retinal cell classes maturation state we assumed the working hypothesis that that maturation of retinal ganglion cells is a continuous, non-discrete process. We have assembled the scRNAseq atlas of human fetal retina from fetal week 8 to week 27 and applied the computational methods to unravel maturation heterogeneity into a uniform maturation track. We align RGC transcriptomes in pseudotime to map RGC developmental fate trajectories against the broader timeline of retinal development. Through this analysis, we identified the continuous maturation track of RGC and described the cell-intrinsic (DEGs, maturation gene profiles, regulons, transcriptional motifs) and -extrinsic profiles (neurotrophic receptors across maturation, cell-cell interactions) of different RGC maturation states. We described the genes involved in the retina and RGC maturation, including de novo RGC maturation drivers. We demonstrate the application of the human fetal retina atlas as a reference tool, allowing automated annotation and universal embedding of scRNAseq data. Altogether, our findings deepen the current knowledge of the retina and RGC maturation by bringing in the maturation dimension for the cell class vs. state analysis. We show how the pseudotime application contributes to developmental-oriented analyses, allowing to order the cells by their maturation state. This approach not only improves the downstream computational analysis but also provides a true maturation track transcriptomics profile.","doi":"10.1016/j.ydbio.2025.08.025","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://bnv-lab.org/data"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/mcrewcow/fetal_retina_PODs_Soucy_Kriukov"},{"link_name":"Sridhar et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1016/j.celrep.2020.01.007"},{"link_name":"Lu et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1016/j.devcel.2020.04.009"}],"name":"Human fetal retina atlas v1 - Unraveling the developmental heterogeneity within the human retina to reconstruct the continuity of retinal ganglion cell maturation and stage-specific intrinsic and extrinsic factors","published_at":"2025-10-01T23:21:11+00:00","publisher_metadata":{"authors":[{"family":"Kriukov","given":"Emil"},{"family":"Soucy","given":"Jonathan R."},{"family":"Labrecque","given":"Everett"},{"family":"Baranov","given":"Petr"}],"is_preprint":false,"journal":"Developmental Biology","published_at":1764547200.0,"published_day":1,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:52:38+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"6f6d381a-7701-4781-935c-db10d30de293","collection_url":"https://cellxgene.cziscience.com/collections/6f6d381a-7701-4781-935c-db10d30de293","collection_version_id":"3e480820-4fd0-4722-84e3-4602f8c28a70","consortia":["CZI Cell Science","Human Cell Atlas (HCA)"],"contact_email":"malte.luecken@helmholtz-muenchen.de","contact_name":"Malte D. 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It consists of over 2 million cells  from the respiratory tract of 486 individuals, and includes 49 different datasets. It is split into the HLCA core, and the extended or full HLCA.\nThe HLCA core includes data of healthy lung tissue from 107 individuals, and includes manual cell type annotations based on consensus across 6 independent experts, as well as demographic, biological and technical metadata. The datasets in the HLCA core were integrated using scANVI. The HLCA core can be used as a reference to map new datasets onto using scArches.\nThe full HLCA includes 35 further  datasets that include donors with various lung diseases. These datasets were mapped onto the core with scArches, and include disease annotations as well as cell type annotations transferred from the HLCA core onto the mapped datasets.\nNote that while the the HLCA includes an integrated, batch-correctd low-dimensional embedding, the gene counts themselves were not batch-corrected. Both the HLCA core and the full HLCA can be explored below. Detailed information about all metadata in the objects, as well as further HLCA-related information , can be found on the HLCA landing page: https://github.com/LungCellAtlas/HLCA. Raw counts are available in the downloaded .h5ad at adata.raw.X, in the downloaded .rds at seurat_object@assays$RNA@counts, and via CELLxGENE Census.","doi":"10.1038/s41591-023-02327-2","is_pre_analysis":false,"links":[{"link_name":"HLCA landing page","link_type":"OTHER","link_url":"https://github.com/LungCellAtlas/HLCA"}],"name":"The integrated Human Lung Cell Atlas","published_at":"2022-03-11T16:47:39+00:00","publisher_metadata":{"authors":[{"family":"Sikkema","given":"Lisa"},{"family":"Ram\u00edrez-Su\u00e1stegui","given":"Ciro"},{"family":"Strobl","given":"Daniel C."},{"family":"Gillett","given":"Tessa E."},{"family":"Zappia","given":"Luke"},{"family":"Madissoon","given":"Elo"},{"family":"Markov","given":"Nikolay S."},{"family":"Zaragosi","given":"Laure-Emmanuelle"},{"family":"Ji","given":"Yuge"},{"family":"Ansari","given":"Meshal"},{"family":"Arguel","given":"Marie-Jeanne"},{"family":"Apperloo","given":"Leonie"},{"family":"Banchero","given":"Martin"},{"family":"B\u00e9cavin","given":"Christophe"},{"family":"Berg","given":"Marijn"},{"family":"Chichelnitskiy","given":"Evgeny"},{"family":"Chung","given":"Mei-i"},{"family":"Collin","given":"Antoine"},{"family":"Gay","given":"Aurore C. A."},{"family":"Gote-Schniering","given":"Janine"},{"family":"Hooshiar Kashani","given":"Baharak"},{"family":"Inecik","given":"Kemal"},{"family":"Jain","given":"Manu"},{"family":"Kapellos","given":"Theodore S."},{"family":"Kole","given":"Tessa M."},{"family":"Leroy","given":"Sylvie"},{"family":"Mayr","given":"Christoph H."},{"family":"Oliver","given":"Amanda J."},{"family":"von Papen","given":"Michael"},{"family":"Peter","given":"Lance"},{"family":"Taylor","given":"Chase J."},{"family":"Walzthoeni","given":"Thomas"},{"family":"Xu","given":"Chuan"},{"family":"Bui","given":"Linh T."},{"family":"De Donno","given":"Carlo"},{"family":"Dony","given":"Leander"},{"family":"Faiz","given":"Alen"},{"family":"Guo","given":"Minzhe"},{"family":"Gutierrez","given":"Austin J."},{"family":"Heumos","given":"Lukas"},{"family":"Huang","given":"Ni"},{"family":"Ibarra","given":"Ignacio L."},{"family":"Jackson","given":"Nathan D."},{"family":"Kadur Lakshminarasimha 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L."},{"family":"Teichmann","given":"Sara A."},{"family":"Misharin","given":"Alexander V."},{"family":"Nawijn","given":"Martijn C."},{"family":"Luecken","given":"Malte D."},{"family":"Theis","given":"Fabian J."},{"name":"Lung Biological Network Consortium"}],"is_preprint":false,"journal":"Nat Med","published_at":1686182400.0,"published_day":8,"published_month":6,"published_year":2023},"revised_at":"2026-06-11T16:52:43+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"1d1c7275-476a-49e2-9022-ad1b1c793594","collection_url":"https://cellxgene.cziscience.com/collections/1d1c7275-476a-49e2-9022-ad1b1c793594","collection_version_id":"f5b207b1-c397-474e-a152-dac848637920","consortia":["CZI Cell Science"],"contact_email":"wey334@g.harvard.edu","contact_name":"Wenjun Yan","created_at":"2026-06-10T15:56:46+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]}],"description":"Most irreversible blindness results from retinal disease. To advance our understanding of the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the transcriptomes of ~85,000 cells from the fovea and peripheral retina of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal ganglion and non-neuronal cells. Nearly all types are shared between the two retinal regions, but there are notable differences in gene expression and proportions between foveal and peripheral cohorts of shared types. We then used the human retinal atlas to map expression of 636 genes implicated as causes of or risk factors for blinding diseases. Many are expressed in striking cell class-, type-, or region-specific patterns. Finally, we compared gene expression signatures of cell types between human and the cynomolgus macaque monkey, Macaca fascicularis. We show that over 90% of human types correspond transcriptomically to those previously identified in macaque, and that expression of disease-related genes is largely conserved between the two species. These results validate the use of the macaque for modeling blinding disease, and provide a foundation for investigating molecular mechanisms underlying visual processing.","doi":"10.1038/s41598-020-66092-9","is_pre_analysis":false,"links":[{"link_name":"GSE148077","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148077"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP839/cell-atlas-of-the-human-fovea-and-peripheral-retina"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/30dc3964-1135-4b56-b393-ce2dcbc6e379"}],"name":"Cell Atlas of The Human Fovea and Peripheral Retina","published_at":"2023-02-10T21:45:48+00:00","publisher_metadata":{"authors":[{"family":"Yan","given":"Wenjun"},{"family":"Peng","given":"Yi-Rong"},{"family":"van 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Multi-site tissue samples were collected from patients undergoing pre-treatment laparoscopy or primary debulking surgeries. Samples are untreated and include primary adnexal tumors (ovary and fallopian tube), metastatic sites (omentum, bowel, pelvic peritoneum, upper quadrants), and ascites.","doi":"10.1038/s41586-022-05496-1","is_pre_analysis":false,"links":[{"link_name":"dbGaP phs002857","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002857"},{"link_name":"","link_type":"OTHER","link_url":"https://www.synapse.org/#!Synapse:syn25569736"},{"link_name":"GSE180661","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE180661"},{"link_name":"MSK SPECTRUM","link_type":"OTHER","link_url":"https://componcmsk.org/msk-spectrum/"},{"link_name":"cBioPortal: WGS, MSK-IMPACT visualization","link_type":"OTHER","link_url":"https://www.cbioportal.org/study/summary?id=msk_spectrum_tme_2022"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/shahcompbio/spectrum-tme"}],"name":"MSK SPECTRUM \u2013 Ovarian cancer mutational processes drive site-specific immune evasion","published_at":"2022-12-20T19:49:19+00:00","publisher_metadata":{"authors":[{"family":"V\u00e1zquez-Garc\u00eda","given":"Ignacio"},{"family":"Uhlitz","given":"Florian"},{"family":"Ceglia","given":"Nicholas"},{"family":"Lim","given":"Jamie L. 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However, the prevalence of these antibodies, their longitudinal dynamics across the disease severity scale, and their functional effects on circulating leukocytes remain unknown. Here, in 284 patients with COVID-19, we found type I IFN-specific autoantibodies in peripheral blood samples from 19% of patients with critical disease and 6% of patients with severe disease. We found no type I IFN autoantibodies in individuals with moderate disease. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 patients with COVID-19 and 26 non-COVID-19 controls revealed a lack of type I IFN-stimulated gene (ISG-I) responses in myeloid cells from patients with critical disease. This was especially evident in dendritic cell populations isolated from patients with critical disease producing type I IFN-specific autoantibodies. Moreover, we found elevated expression of the inhibitory receptor leukocyte-associated immunoglobulin-like receptor 1 (LAIR1) on the surface of monocytes isolated from patients with critical disease early in the disease course. LAIR1 expression is inversely correlated with ISG-I expression response in patients with COVID-19 but is not expressed in healthy controls. The deficient ISG-I response observed in patients with critical COVID-19 with and without type I IFN-specific autoantibodies supports a unifying model for disease pathogenesis involving ISG-I suppression through convergent mechanisms.","doi":"10.1126/scitranslmed.abh2624","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"http://www.protocols.io/view/10x-citeseq-protocol-covid-19-patient-samples-tetr-bqnqmvdw"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=covid19-type1-ifn"},{"link_name":"Code","link_type":"OTHER","link_url":"http://dx.doi.org/10.5281/zenodo.5148862"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168453"}],"name":"Type I interferon autoantibodies are associated with systemic immune alterations in patients with COVID-19","published_at":"2021-06-25T02:50:34+00:00","publisher_metadata":{"authors":[{"family":"van der Wijst","given":"Monique G. P."},{"family":"Vazquez","given":"Sara E."},{"family":"Hartoularos","given":"George C."},{"family":"Bastard","given":"Paul"},{"family":"Grant","given":"Tianna"},{"family":"Bueno","given":"Raymund"},{"family":"Lee","given":"David S."},{"family":"Greenland","given":"John R."},{"family":"Sun","given":"Yang"},{"family":"Perez","given":"Richard"},{"family":"Ogorodnikov","given":"Anton"},{"family":"Ward","given":"Alyssa"},{"family":"Mann","given":"Sabrina A."},{"family":"Lynch","given":"Kara L."},{"family":"Yun","given":"Cassandra"},{"family":"Havlir","given":"Diane V."},{"family":"Chamie","given":"Gabriel"},{"family":"Marquez","given":"Carina"},{"family":"Greenhouse","given":"Bryan"},{"family":"Lionakis","given":"Michail S."},{"family":"Norris","given":"Philip J."},{"family":"Dumont","given":"Larry J."},{"family":"Kelly","given":"Kathleen"},{"family":"Zhang","given":"Peng"},{"family":"Zhang","given":"Qian"},{"family":"Gervais","given":"Adrian"},{"family":"Le Voyer","given":"Tom"},{"family":"Whatley","given":"Alexander"},{"family":"Si","given":"Yichen"},{"family":"Byrne","given":"Ashley"},{"family":"Combes","given":"Alexis J."},{"family":"Rao","given":"Arjun Arkal"},{"family":"Song","given":"Yun S."},{"family":"Fragiadakis","given":"Gabriela K."},{"family":"Kangelaris","given":"Kirsten"},{"family":"Calfee","given":"Carolyn S."},{"family":"Erle","given":"David J."},{"family":"Hendrickson","given":"Carolyn"},{"family":"Krummel","given":"Matthew F."},{"family":"Woodruff","given":"Prescott G."},{"family":"Langelier","given":"Charles R."},{"family":"Casanova","given":"Jean-Laurent"},{"family":"Derisi","given":"Joseph L."},{"family":"Anderson","given":"Mark S."},{"family":"Ye","given":"Chun Jimmie"},{"name":"on behalf of the UCSF COMET consortium"}],"is_preprint":false,"journal":"Sci. Transl. Med.","published_at":1632268800.0,"published_day":22,"published_month":9,"published_year":2021},"revised_at":"2026-06-11T16:54:11+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e1a9ca56-f2ee-435d-980a-4f49ab7a952b","collection_url":"https://cellxgene.cziscience.com/collections/e1a9ca56-f2ee-435d-980a-4f49ab7a952b","collection_version_id":"485786c2-94b3-4bdb-a1d9-54ddd5aa9eed","consortia":[],"contact_email":"marina.sirota@ucsf.edu","contact_name":"Marina Sirota","created_at":"2026-06-10T07:10:18+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d18736c3-6292-4379-919a-d6d973204c87","dataset_version_id":"3b751975-34bb-409a-a9b7-98380f0450ea","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"rheumatoid arthritis","ontology_term_id":"MONDO:0008383"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Rheumatoid arthritis (RA) management lean toward achieving remission or low-disease activity. In this study, we conducted single-cell RNA sequencing (scRNAseq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 RA patients and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type- specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFITM3 overexpressing Interferon-activated (IFN-activated) monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate to high disease activity (DAS28-CRP \u2265 3.2), and a decrease in non-classical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of pro-inflammatory genes in the gamma-delta T cells subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and non-classical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of pro-inflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, G0S2, and downregulation of genes including HLA-DQB1, HLA-DRB5, TNFSF13B. Notably, cell- cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.","doi":"10.1172/jci.insight.178499","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/BMiao10/RASingleCell"}],"name":"Single-cell RNA-seq analysis reveals cell subsets and gene signatures associated with Rheumatoid Arthritis Disease Activity","published_at":"2024-08-19T23:23:33+00:00","publisher_metadata":{"authors":[{"family":"Binvignat","given":"Marie"},{"family":"Miao","given":"Brenda Y."},{"family":"Wibrand","given":"Camilla"},{"family":"Yang","given":"Monica M."},{"family":"Rychkov","given":"Dmitry"},{"family":"Flynn","given":"Emily"},{"family":"Nititham","given":"Joanne"},{"family":"Tamaki","given":"Whitney"},{"family":"Khan","given":"Umair"},{"family":"Carvidi","given":"Alexander"},{"family":"Krueger","given":"Melissa"},{"family":"Niemi","given":"Erene"},{"family":"Sun","given":"Yang"},{"family":"Fragiadakis","given":"Gabriela K."},{"family":"Sellam","given":"J\u00e9r\u00e9mie"},{"family":"Mariotti-Ferrandiz","given":"Encarnita"},{"family":"Klatzmann","given":"David"},{"family":"Gross","given":"Andrew J."},{"family":"Ye","given":"Chun Jimmie"},{"family":"Butte","given":"Atul J."},{"family":"Criswell","given":"Lindsey A."},{"family":"Nakamura","given":"Mary C."},{"family":"Sirota","given":"Marina"}],"is_preprint":false,"journal":"JCI Insight","published_at":1724284800.0,"published_day":22,"published_month":8,"published_year":2024},"revised_at":"2026-06-11T16:54:03+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e77163ca-8214-4e86-8b37-4f65a2ddae13","collection_url":"https://cellxgene.cziscience.com/collections/e77163ca-8214-4e86-8b37-4f65a2ddae13","collection_version_id":"7169cfce-7251-431f-a209-6f8dcd70065c","consortia":[],"contact_email":"Britt.Anne.Goods@dartmouth.edu","contact_name":"Brittany A. Goods","created_at":"2026-06-10T06:31:06+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"Seq-Well","ontology_term_id":"EFO:0008919"}],"dataset_id":"0920bcb8-4b3a-4e9d-a353-56f529fd3b32","dataset_version_id":"7965ced3-d4cd-4c0c-9f76-3a724f9cd2fb","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"milk","ontology_term_id":"UBERON:0001913","tissue_type":"tissue"}]}],"description":"Human breast milk (hBM) is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We generated and analyzed single-cell RNA-sequencing (scRNA-seq) data to characterize the transcriptomes of cells from hBM across lactational time from 3 to 632 d postpartum in 15 donors. We found that the majority of cells in hBM are lactocytes, a specialized epithelial subset, and that cell-type frequencies shift over the course of lactation, yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone-, growth factor-, and milk production-related pathways. Generalized additive models suggest that one subcluster, LC1 epithelial cells, increases as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several subclusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal\u2013infant dyad metadata, and our quantification of alterations at the gene and pathway levels provide a detailed longitudinal picture of hBM cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.","doi":"10.1073/pnas.2121720119","is_pre_analysis":false,"links":[{"link_name":"DUOS-000140","link_type":"RAW_DATA","link_url":"https://duos.org/dataset/DUOS-000140"},{"link_name":"SCP1671","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1671"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/ShalekLab/MIT_Milk_Study"}],"name":"Cellular and transcriptional diversity over the course of human lactation","published_at":"2024-07-09T19:14:49+00:00","publisher_metadata":{"authors":[{"family":"Nyquist","given":"Sarah K."},{"family":"Gao","given":"Patricia"},{"family":"Haining","given":"Tessa K. 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Using single cell RNA-sequencing, we identified and validated the in situ localization of three smooth muscle subtypes (prostate smooth muscle, pericytes, and vascular smooth muscle) and two novel fibroblast subtypes in human prostate. Peri-epithelial fibroblasts (APOD+) wrap around epithelial structures while interstitial fibroblasts (C7+) are interspersed in extracellular matrix. In contrast, the mouse displayed three fibroblast subtypes with distinct proximal-distal and lobe specific distribution patterns. Statistical analysis of mouse and human fibroblasts showed transcriptional correlation between mouse prostate (C3+) and urethral (Lgr5+) fibroblasts and the human interstitial fibroblast subtype. Both urethral fibroblasts (Lgr5+) and ductal fibroblasts (Wnt2+) in the mouse contribute to a proximal Wnt/Tgfb signaling niche that is absent in human prostate. Instead, human peri-epithelial fibroblasts express secreted WNT inhibitors SFRPs and DKK1, which could serve as a buffer against stromal WNT ligands by creating a localized signaling niche around individual prostate glands. We also identified proximal-distal fibroblast density differences in human prostate that could amplify stromal signaling around proximal prostate ducts. In human Benign Prostatic Hyperplasia, fibroblast subtypes upregulate critical immunoregulatory pathways and show distinct distributions in stromal and glandular phenotypes. A detailed taxonomy of leukocytes in BPH reveals an influx of myeloid dendritic cells, T cells and B cells, resembling a mucosal inflammatory disorder. A receptor-ligand interaction analysis of all cell types revealed a central role for fibroblasts in growth factor, morphogen and chemokine signaling to endothelia, epithelia, and leukocytes. These data are foundational to the development of new therapeutic targets in benign prostatic hyperplasia.","doi":"10.1002/path.5751","is_pre_analysis":false,"links":[{"link_name":"www.gudmap.org","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.25548/17-DRBC"},{"link_name":"Human Raw Data","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE172357"},{"link_name":"Mouse Raw Data","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173096"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://strandlab.net/"}],"name":"Single cell analysis of mouse and human prostate reveals novel fibroblasts with specialized distribution and microenvironment interactions","published_at":"2021-07-06T19:51:45+00:00","publisher_metadata":{"authors":[{"family":"Joseph","given":"Diya B"},{"family":"Henry","given":"Gervaise H"},{"family":"Malewska","given":"Alicia"},{"family":"Reese","given":"Jeffrey C"},{"family":"Mauck","given":"Ryan J"},{"family":"Gahan","given":"Jeffrey C"},{"family":"Hutchinson","given":"Ryan C"},{"family":"Malladi","given":"Venkat S"},{"family":"Roehrborn","given":"Claus G"},{"family":"Vezina","given":"Chad M"},{"family":"Strand","given":"Douglas W"}],"is_preprint":false,"journal":"The Journal of Pathology","published_at":1633046400.0,"published_day":1,"published_month":10,"published_year":2021},"revised_at":"2026-06-11T16:53:14+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"1a486c4c-c115-4721-8c9f-f9f096e10857","collection_url":"https://cellxgene.cziscience.com/collections/1a486c4c-c115-4721-8c9f-f9f096e10857","collection_version_id":"c9394118-0d32-4f08-8b8c-beff73a988fb","consortia":[],"contact_email":"brian.hafler@yale.edu","contact_name":"Brian P. 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However, it has been challenging to identify the cell types associated with AMD given the genetic complexity of the disease. Here we perform massively parallel single-cell RNA sequencing (scRNA-seq) of human retinas using two independent platforms, and report the first single-cell transcriptomic atlas of the human retina. Using a multi-resolution network-based analysis, we identify all major retinal cell types, and their corresponding gene expression signatures. Heterogeneity is observed within macroglia, suggesting that human retinal glia are more diverse than previously thought. Finally, GWAS-based enrichment analysis identifies glia, vascular cells, and cone photoreceptors to be associated with the risk of AMD. These data provide a detailed analysis of the human retina, and show how scRNA-seq can provide insight into cell types involved in complex, inflammatory genetic diseases.","doi":"10.1038/s41467-019-12780-8","is_pre_analysis":false,"links":[{"link_name":"GSE137537","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137537"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=retina-mac-degen"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-137537"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/07d5987e-7f9e-4f34-b0fb-a185a35504f5"}],"name":"Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration","published_at":"2022-10-19T15:07:07+00:00","publisher_metadata":{"authors":[{"family":"Menon","given":"Madhvi"},{"family":"Mohammadi","given":"Shahin"},{"family":"Davila-Velderrain","given":"Jose"},{"family":"Goods","given":"Brittany A."},{"family":"Cadwell","given":"Tanina D."},{"family":"Xing","given":"Yu"},{"family":"Stemmer-Rachamimov","given":"Anat"},{"family":"Shalek","given":"Alex K."},{"family":"Love","given":"John Christopher"},{"family":"Kellis","given":"Manolis"},{"family":"Hafler","given":"Brian P."}],"is_preprint":false,"journal":"Nat Commun","published_at":1575158400.0,"published_day":1,"published_month":12,"published_year":2019},"revised_at":"2026-06-11T16:54:08+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e9cf4e8d-05ed-4d95-b550-af35ca219390","collection_url":"https://cellxgene.cziscience.com/collections/e9cf4e8d-05ed-4d95-b550-af35ca219390","collection_version_id":"3464db4e-9883-41be-ab7c-ccf250800e81","consortia":["Human Cell Atlas (HCA)"],"contact_email":"lungdrcho@snu.ac.kr","contact_name":"Young-Jae CHO","created_at":"2026-06-10T04:20:51+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ef1a4b05-540c-4f73-8ceb-49dfa800645d","dataset_version_id":"d3b2dfdb-e189-4257-8fab-083f7dbea4e3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"epithelial cell of lung","ontology_term_id":"CL:0000082","tissue_type":"primary cell culture"},{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"organoid"}]}],"description":"We comprehensively analyzed differentiation effects of the air\u2013liquid interface (ALI) culture method on adult tissue-derived human lung organoids compared to 3 distinct submerged cultures using scRNA-seq. The fresh normal lung tissues from two individuals were collected for lung organoid culture and four distinct culture models were generated for each. Chromium Single Cell 3\u2019 (10X genomics) and NovaSeq-6000 system (Illumina) through paired-end reads were used. SCTransform (v2) was used for normalization.","doi":"10.3390/cells13231991","is_pre_analysis":false,"links":[{"link_name":"GSE280502","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE280502"}],"name":"Transcriptomic Analysis of Air-Liquid Interface Culture in Human Lung Organoids Reveals Regulators of Epithelial Differentiation","published_at":"2024-12-06T23:14:31+00:00","publisher_metadata":{"authors":[{"family":"Kim","given":"Jieun"},{"family":"Eo","given":"Eun-Young"},{"family":"Kim","given":"Bokyong"},{"family":"Lee","given":"Heetak"},{"family":"Kim","given":"Jihoon"},{"family":"Koo","given":"Bon-Kyoung"},{"family":"Kim","given":"Hyung-Jun"},{"family":"Cho","given":"Sukki"},{"family":"Kim","given":"Jinho"},{"family":"Cho","given":"Young-Jae"}],"is_preprint":false,"journal":"Cells","published_at":1733097600.0,"published_day":2,"published_month":12,"published_year":2024},"revised_at":"2026-06-11T16:54:09+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"fe0e718d-2ee9-42cc-894b-0b490f437dfd","collection_url":"https://cellxgene.cziscience.com/collections/fe0e718d-2ee9-42cc-894b-0b490f437dfd","collection_version_id":"0b69d863-f3aa-455c-be5c-c0add71bfe2b","consortia":[],"contact_email":"erosen@bidmc.harvard.edu","contact_name":"Evan D. 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High fat feeding and other metabolic stressors cause dramatic changes in adipose morphology, physiology, and cellular composition, and alterations in adiposity are associated with insulin resistance, dyslipidemia, and Type 2 diabetes (T2D). Here we provide detailed cellular atlases of human and murine subcutaneous and visceral white fat at single cell resolution across a range of body weight.  We identify subpopulations of adipocytes, adipose stem and progenitor cells (ASPCs), vascular, and immune cells and demonstrate commonalities and differences across species and dietary conditions.  We link specific cell types to increased risk of metabolic disease, and we provide an initial blueprint for a comprehensive set of interactions between individual cell types in the adipose niche in leanness and obesity.  These data comprise a extensive resource for the exploration of genes, traits, and cell types in the function of WAT across species, depots, and nutritional conditions.","doi":"10.1038/s41586-022-04518-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1376"},{"link_name":"","link_type":"OTHER","link_url":"https://gitlab.com/rosen-lab/white-adipose-atlas"},{"link_name":"scRNA-seq (GSE176067)","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176067"},{"link_name":"sNuc-seq (GSE176171)","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176171"},{"link_name":"phs002766","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002766"}],"name":"A single-cell atlas of human and mouse white adipose 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Here, we generated a high-resolution cell atlas of brain aging within the frontal cortex and striatum using spatially resolved single-cell transcriptomics and quantified changes in gene expression and spatial organization of major cell types in these regions over the mouse lifespan. We observed substantially more pronounced changes in cell state, gene expression, and spatial organization of non-neuronal cells over neurons. Our data revealed molecular and spatial signatures of glial and immune cell activation during aging, particularly enriched in the subcortical white matter, and identified both similarities and notable differences in cell-activation patterns induced by aging and systemic inflammatory challenge. These results provide critical insights into age-related decline and inflammation in the brain.","doi":"10.1016/j.cell.2022.12.010","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ZhuangLab/SpatialBrainAgingCell22"},{"link_name":"GSE207848","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE207848"}],"name":"Molecular and spatial signatures of mouse brain aging at single-cell resolution","published_at":"2023-01-04T17:37:13+00:00","publisher_metadata":{"authors":[{"family":"Allen","given":"William E."},{"family":"Blosser","given":"Timothy R."},{"family":"Sullivan","given":"Zuri 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The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system and its responsiveness that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases.  As part of our study on immune dynamics across healthy age (link), we generated the Human Immune Health Atlas \u2013 a single cell RNA-seq dataset from > 1.8 million peripheral blood mononuclear cells obtained from 108 healthy pediatric, young adult, and older adult donors with no history of chronic or autoimmune disease, chronic infections, or severe allergy, allowing deeper interrogation of the composition and transcriptional state of 71 unique human immune cell subsets. This resource and associated tools are available at https://apps.allenimmunology.org/aifi/resources/imm-health-atlas/.","doi":"10.1038/s41586-025-09686-5","is_pre_analysis":false,"links":[{"link_name":"Human Immune Health Atlas","link_type":"OTHER","link_url":"https://apps.allenimmunology.org/aifi/resources/imm-health-atlas/"},{"link_name":"Human Immune Health Atlas github","link_type":"OTHER","link_url":"https://github.com/aifimmunology/aifi-healthy-pbmc-reference/"},{"link_name":"Dynamics of IHA Collection","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/e9360edf-b0b7-4e01-bce8-e596814f13e7"},{"link_name":"phs003841","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003841"},{"link_name":"GSE275067","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE275067"}],"name":"Human Immune Health Atlas","published_at":"2025-10-24T23:35:58+00:00","publisher_metadata":{"authors":[{"family":"Gong","given":"Qiuyu"},{"family":"Sharma","given":"Mehul"},{"family":"Glass","given":"Marla C."},{"family":"Kuan","given":"Emma L."},{"family":"Chander","given":"Aishwarya"},{"family":"Singh","given":"Mansi"},{"family":"Graybuck","given":"Lucas T."},{"family":"Thomson","given":"Zachary J."},{"family":"LaFrance","given":"Christian M."},{"family":"Rachid Zaim","given":"Samir"},{"family":"Peng","given":"Tao"},{"family":"Okada","given":"Lauren Y."},{"family":"Genge","given":"Palak C."},{"family":"Henderson","given":"Katherine E."},{"family":"Dornisch","given":"Elisabeth M."},{"family":"Layton","given":"Erik D."},{"family":"Wittig","given":"Peter J."},{"family":"Heubeck","given":"Alexander T."},{"family":"Mukuka","given":"Nelson M."},{"family":"Reading","given":"Julian"},{"family":"Strawn","given":"Garrett"},{"family":"Titus-Adewunmi","given":"Teminijesu"},{"family":"Abadie","given":"Kathleen"},{"family":"Roll","given":"Charles R."},{"family":"Hernandez","given":"Veronica"},{"family":"Parthasarathy","given":"Vaishnavi"},{"family":"Stuckey","given":"Tyanna J."},{"family":"Musgrove","given":"Blessing"},{"family":"Swanson","given":"Elliott"},{"family":"Lord","given":"Cara"},{"family":"Weiss","given":"Morgan D. A."},{"family":"Phalen","given":"Cole G."},{"family":"Mettey","given":"Regina R."},{"family":"Lee","given":"Kevin J."},{"family":"Johanneson","given":"John B."},{"family":"Kawelo","given":"Erin K."},{"family":"Garber","given":"Jessica"},{"family":"Krishnan","given":"Upaasana"},{"family":"Smithmyer","given":"Megan"},{"family":"Wherry","given":"E. John"},{"family":"Vella","given":"Laura A."},{"family":"Henrickson","given":"Sarah E."},{"family":"Kopp","given":"Mackenzie S."},{"family":"Savage","given":"Adam K."},{"family":"Becker","given":"Lynne A."},{"family":"Meijer","given":"Paul"},{"family":"Coffey","given":"Ernest M."},{"family":"Goronzy","given":"Jorg J."},{"family":"Sigvardsson","given":"Mikael"},{"family":"Speake","given":"Cate"},{"family":"Bumol","given":"Thomas F."},{"family":"Goldrath","given":"Ananda W."},{"family":"Torgerson","given":"Troy R."},{"family":"Li","given":"Xiao-jun"},{"family":"Skene","given":"Peter J."},{"family":"Buckner","given":"Jane H."},{"family":"Gustafson","given":"Claire E."}],"is_preprint":false,"journal":"Nature","published_at":1766016000.0,"published_day":18,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:54:12+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ff69f0ee-fef6-4895-9f48-6c64a68c8289","collection_url":"https://cellxgene.cziscience.com/collections/ff69f0ee-fef6-4895-9f48-6c64a68c8289","collection_version_id":"1e2bece8-b5dc-4041-b15f-bb9651182f59","consortia":["CZI Cell Science"],"contact_email":"s.macparland@utoronto.ca","contact_name":"Sonya MacParland","created_at":"2026-06-10T02:22:10+00:00","curator_name":"emruther@stanford.edu","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"84cfa5aa-a0d1-415e-ac47-eb66c9cf8170","dataset_version_id":"91a9f46f-2272-4f6b-9e08-7aae2debba87","disease":[{"label":"intestinal failure\u2013associated liver disease","ontology_term_id":"MONDO:0100615"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"left lobe of liver","ontology_term_id":"UBERON:0001115","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"120cbe1a-9434-4e23-84bd-f570ac32300c","dataset_version_id":"500364df-df28-4e3c-85a7-6f702ed1a0d9","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"},{"label":"right lobe of liver","ontology_term_id":"UBERON:0001114","tissue_type":"tissue"}]}],"description":"Background: \nThe liver plays a critical role in metabolism and immune function, yet the contributions of its heterogeneous cell types to these processes remain unclear. While most liver studies focus on adults, pediatric liver diseases often present differently, underscoring the need for age-specific research.\n\nMethods: \nTo better understand cellular drivers of childhood liver diseases, we generated single-cell RNA-sequencing maps of the normal pediatric liver and used this map to examine disease-related populations in biopsies from pediatric patients with intestinal failure\u2013associated liver disease (IFALD).\n\nResults: \nThe normal pediatric liver map consists of 42,660 cells from 9 donors under 17 years of age. Compared with normal adult liver (26,372 cells; 7 donors, age 26\u201369), pediatric livers exhibited differences in myeloid populations. Specifically, pediatric Kupffer-like cells (MARCO+C1QA+VSIG4+) exhibited higher expression of immune activation genes, including CCL4, CCL3, and IL1B. In vitro stimulation confirmed more IL-1\u03b2-secreting myeloid cells in pediatric versus adult livers, supporting these findings. Using the pediatric atlas as a reference, we analyzed 3 IFALD biopsies (11,969 cells; 3 donors, under 9 y of age) and identified increased expression of fibrosis-associated genes (eg, LY96) in Kupffer-like cells. In addition, mesenchymal cells in IFALD showed fibrotic gene modules resembling adult liver cells more than healthy pediatric cells. These signatures, undetectable when comparing IFALD to adult liver alone, highlight the value of a pediatric map.\n\nConclusion: \nTaken together, our healthy pediatric liver atlas reveals distinct age-related signatures and provides a background against which to interpret pediatric liver disease data.","doi":"10.1097/HC9.0000000000000813","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/human-liver-caudate-lobe-dissociation-for-scrna-se-q26g77j1gwz1/v2"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/human-liver-core-needle-biopsy-processing-protocol-8epv5jzwjl1b/v1"}],"name":"Single-Cell Atlas Of Human Pediatric Liver Reveals Age-Related Hepatic Gene Signatures","published_at":"2025-07-23T18:14:40+00:00","publisher_metadata":{"authors":[{"family":"Edgar","given":"Rachel D."},{"family":"Nakib","given":"Diana"},{"family":"Camat","given":"Damra"},{"family":"Chung","given":"Sai"},{"family":"Lumanto","given":"Patricia"},{"family":"Atif","given":"Jawairia"},{"family":"Perciani","given":"Catia T."},{"family":"Ma","given":"Xue-Zhong"},{"family":"Thoeni","given":"Cornelia"},{"family":"Selvakumaran","given":"Nilosa"},{"family":"Manuel","given":"Justin"},{"family":"Sayed","given":"Blayne"},{"family":"Huysentruyt","given":"Koen"},{"family":"Ricciuto","given":"Amanda"},{"family":"McGilvray","given":"Ian"},{"family":"Avitzur","given":"Yaron"},{"family":"Bader","given":"Gary D."},{"family":"MacParland","given":"Sonya A."}],"is_preprint":false,"journal":"Hepatology Communications","published_at":1759795200.0,"published_day":7,"published_month":10,"published_year":2025},"revised_at":"2026-06-11T16:53:20+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"296237e2-393d-4e31-b590-b03f74ac5070","collection_url":"https://cellxgene.cziscience.com/collections/296237e2-393d-4e31-b590-b03f74ac5070","collection_version_id":"5d211b84-a430-4569-9fe0-2b43e396753a","consortia":[],"contact_email":"karin.hrovatin@helmholtz-muenchen.de","contact_name":"Karin Hrovatin","created_at":"2026-06-10T04:13:25+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"49e4ffcc-5444-406d-bdee-577127404ba8","dataset_version_id":"2cf0b367-e31b-4ab3-8557-8f2c4ac2a31a","disease":[{"label":"endocrine pancreas disorder","ontology_term_id":"MONDO:0001933"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"type 1 diabetes mellitus","ontology_term_id":"MONDO:0005147"},{"label":"type 2 diabetes mellitus","ontology_term_id":"MONDO:0005148"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"},{"label":"pancreas","ontology_term_id":"UBERON:0001264","tissue_type":"tissue"}]}],"description":"To better understand pancreatic \u03b2-cell heterogeneity we generated a mouse pancreatic islet atlas capturing a wide range of biological conditions. The atlas contains scRNA-seq datasets of over 300,000 mouse pancreatic islet cells, of which more than 100,000 are \u03b2-cells, from nine datasets with 56 samples, including two previously unpublished datasets. The samples vary in sex, age (ranging from embryonic to aged), chemical stress, and disease status (including T1D NOD model development and two T2D models, mSTZ and db/db) together with different diabetes treatments. Additional information about data fields is available in anndata uns field 'field_descriptions' and on https://github.com/theislab/mm_pancreas_atlas_rep/blob/main/resources/cellxgene.md","doi":"10.1038/s42255-023-00876-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/theislab/mm_pancreas_atlas_rep"},{"link_name":"GSE211799","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE211799"}],"name":"Mouse pancreatic islet scRNA-seq atlas across sexes, ages, and stress conditions including diabetes","published_at":"2023-01-05T20:09:58+00:00","publisher_metadata":{"authors":[{"family":"Hrovatin","given":"Karin"},{"family":"Bastidas-Ponce","given":"Aim\u00e9e"},{"family":"Bakhti","given":"Mostafa"},{"family":"Zappia","given":"Luke"},{"family":"B\u00fcttner","given":"Maren"},{"family":"Salinno","given":"Ciro"},{"family":"Sterr","given":"Michael"},{"family":"B\u00f6ttcher","given":"Anika"},{"family":"Migliorini","given":"Adriana"},{"family":"Lickert","given":"Heiko"},{"family":"Theis","given":"Fabian J."}],"is_preprint":false,"journal":"Nat Metab","published_at":1694390400.0,"published_day":11,"published_month":9,"published_year":2023},"revised_at":"2026-06-11T16:54:13+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"f5af7a2f-ab4c-4728-829e-48efb9562105","collection_url":"https://cellxgene.cziscience.com/collections/f5af7a2f-ab4c-4728-829e-48efb9562105","collection_version_id":"6294a2c9-8eaa-4986-9a86-4200a6d9b5b8","consortia":[],"contact_email":"Yanling_Liao@nymc.edu","contact_name":"Yanling Liao","created_at":"2026-06-10T00:44:58+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7be2824e-d62a-42ef-9169-084555c6df87","dataset_version_id":"2965d8bb-05c5-40a1-bb03-c0b568cb1919","disease":[{"label":"epidermolysis bullosa","ontology_term_id":"MONDO:0006541"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"autopod skin","ontology_term_id":"UBERON:0015790","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"6beff4d6-98a8-4f49-8ba7-84d152494a23","dataset_version_id":"1f03f43e-ed22-4caf-8fd9-0805bd958dca","disease":[{"label":"epidermolysis bullosa","ontology_term_id":"MONDO:0006541"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"autopod skin","ontology_term_id":"UBERON:0015790","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5bc26721-894b-4e9a-9423-6ecfd233ab20","dataset_version_id":"5aa8424f-8e20-4cb8-a642-797472a26f0a","disease":[{"label":"epidermolysis bullosa","ontology_term_id":"MONDO:0006541"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"autopod skin","ontology_term_id":"UBERON:0015790","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"389b1fd4-2b65-4f60-baba-feeb17507665","dataset_version_id":"5cc1649e-3a7e-4950-89c4-51f399d9ed25","disease":[{"label":"epidermolysis bullosa","ontology_term_id":"MONDO:0006541"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"autopod skin","ontology_term_id":"UBERON:0015790","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"1398f3a9-b48b-431a-a5f2-d4a1931c4b45","dataset_version_id":"266ec864-9638-4479-8b76-8d033d2f63dc","disease":[{"label":"epidermolysis bullosa","ontology_term_id":"MONDO:0006541"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"autopod skin","ontology_term_id":"UBERON:0015790","tissue_type":"tissue"}]}],"description":"Recessive dystrophic epidermolysis bullosa (RDEB) is a genetic disorder caused by loss of function of the Col7a1 gene that encodes collagen VII, a critical structural protein that anchors the epidermis to the dermis. Manifestations of this disease include chronic wounding, blistering, immune dysfunction, and eventually squamous cell carcinoma. Symptoms are likely due to the disruption and dysregulation of the dermal microenvironment. Mice with RDEB symptoms, due to Col7a1 knockout, have been developed to study the disease's development and pathological manifestations in an in vivo model. Single cell RNA sequencing was performed on a single cell suspension of the paw skin of 2 week old RDEB mice, along with their wild-type littermates, to create a transcriptomic view of their dermal microenvironment. We analyzed the sequencing data at different resolutions. One focusing on the overall tissue level as well as closer analysis of specific cell types (fibroblasts, keratinocytes, immune cells, and vascular cells).","doi":"10.3389/fimmu.2023.1211505","is_pre_analysis":false,"links":[{"link_name":"GSE222250","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE222250"}],"name":"Single cell RNA sequencing of paw skin from healthy and Col7a1 knockout (RDEB) mice","published_at":"2024-02-15T23:51:08+00:00","publisher_metadata":{"authors":[{"family":"Anderson-Crannage","given":"Morgan"},{"family":"Ascensi\u00f3n","given":"Alex M."},{"family":"Ibanez-Sol\u00e9","given":"Olga"},{"family":"Zhu","given":"Hongwen"},{"family":"Schaefer","given":"Edo"},{"family":"Ottomanelli","given":"Darcy"},{"family":"Hochberg","given":"Bruno"},{"family":"Pan","given":"Jian"},{"family":"Luo","given":"Wen"},{"family":"Tian","given":"Meijuan"},{"family":"Chu","given":"Yaya"},{"family":"Cairo","given":"Mitchell S."},{"family":"Izeta","given":"Ander"},{"family":"Liao","given":"Yanling"}],"is_preprint":false,"journal":"Front. Immunol.","published_at":1695168000.0,"published_day":20,"published_month":9,"published_year":2023},"revised_at":"2026-06-11T16:53:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"84ce6837-548d-4a1f-919f-0bc0d9a3952f","collection_url":"https://cellxgene.cziscience.com/collections/84ce6837-548d-4a1f-919f-0bc0d9a3952f","collection_version_id":"52ba1325-53e8-4477-9ce0-f50836019a1f","consortia":[],"contact_email":"panagiotis.roussos@mssm.edu","contact_name":"Panos Roussos","created_at":"2026-06-10T09:26:40+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5e57cd50-8e42-42d6-940d-5c1660d06864","dataset_version_id":"54293783-669c-410e-919d-474960f8761b","disease":[{"label":"amyotrophic lateral sclerosis","ontology_term_id":"MONDO:0004976"},{"label":"dementia","ontology_term_id":"MONDO:0001627"},{"label":"dementia || Alzheimer disease","ontology_term_id":"MONDO:0001627 || MONDO:0004975"},{"label":"dementia || Alzheimer disease || Lewy body dementia","ontology_term_id":"MONDO:0001627 || MONDO:0004975 || MONDO:0007488"},{"label":"dementia || Alzheimer disease || Parkinson disease","ontology_term_id":"MONDO:0001627 || MONDO:0004975 || MONDO:0005180"},{"label":"dementia || Alzheimer disease || Parkinson disease || Lewy body dementia","ontology_term_id":"MONDO:0001627 || MONDO:0004975 || MONDO:0005180 || MONDO:0007488"},{"label":"dementia || Alzheimer disease || diabetes mellitus","ontology_term_id":"MONDO:0001627 || MONDO:0004975 || MONDO:0005015"},{"label":"dementia || Alzheimer disease || diabetes mellitus || Parkinson disease || head injury","ontology_term_id":"MONDO:0001627 || MONDO:0004975 || MONDO:0005015 || MONDO:0005180 || MONDO:0800482"},{"label":"dementia || Parkinson disease","ontology_term_id":"MONDO:0001627 || MONDO:0005180"},{"label":"dementia || Parkinson disease || Lewy body dementia || head injury","ontology_term_id":"MONDO:0001627 || MONDO:0005180 || MONDO:0007488 || MONDO:0800482"},{"label":"dementia || diabetes mellitus || Parkinson disease","ontology_term_id":"MONDO:0001627 || MONDO:0005015 || MONDO:0005180"},{"label":"dementia || frontotemporal dementia","ontology_term_id":"MONDO:0001627 || MONDO:0017276"},{"label":"dementia || tauopathy","ontology_term_id":"MONDO:0001627 || MONDO:0005574"},{"label":"dementia || vascular dementia","ontology_term_id":"MONDO:0001627 || MONDO:0004648"},{"label":"dementia || vascular dementia || Alzheimer disease","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0004975"},{"label":"dementia || vascular dementia || Alzheimer disease || Parkinson disease","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0004975 || MONDO:0005180"},{"label":"dementia || vascular dementia || Alzheimer disease || diabetes mellitus","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0004975 || MONDO:0005015"},{"label":"dementia || vascular dementia || diabetes mellitus","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0005015"},{"label":"diabetes mellitus","ontology_term_id":"MONDO:0005015"},{"label":"diabetes mellitus || head injury","ontology_term_id":"MONDO:0005015 || MONDO:0800482"},{"label":"head injury","ontology_term_id":"MONDO:0800482"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"tauopathy","ontology_term_id":"MONDO:0005574"},{"label":"vascular dementia","ontology_term_id":"MONDO:0004648"},{"label":"vascular dementia || diabetes mellitus","ontology_term_id":"MONDO:0004648 || MONDO:0005015"},{"label":"vascular dementia || diabetes mellitus || Parkinson disease","ontology_term_id":"MONDO:0004648 || MONDO:0005015 || MONDO:0005180"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dorsolateral prefrontal cortex","ontology_term_id":"UBERON:0009834","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5c97eeeb-7e52-44b3-b010-b832b1f5424c","dataset_version_id":"d27fb144-f105-46c2-b36f-f51421f74e4e","disease":[{"label":"atherosclerosis","ontology_term_id":"MONDO:0005311"},{"label":"atherosclerosis || tardive dyskinesia || schizoaffective bipolar disorder","ontology_term_id":"MONDO:0005311 || MONDO:0010096 || MONDO:1060151"},{"label":"bipolar I disorder","ontology_term_id":"MONDO:0001866"},{"label":"bipolar I disorder || anorexia nervosa","ontology_term_id":"MONDO:0001866 || MONDO:0005351"},{"label":"bipolar I disorder || anorexia nervosa || obsessive-compulsive disorder","ontology_term_id":"MONDO:0001866 || MONDO:0005351 || MONDO:0008114"},{"label":"bipolar I disorder || atherosclerosis","ontology_term_id":"MONDO:0001866 || MONDO:0005311"},{"label":"bipolar I disorder || attention deficit-hyperactivity disorder","ontology_term_id":"MONDO:0001866 || MONDO:0007743"},{"label":"bipolar I disorder || brain neoplasm","ontology_term_id":"MONDO:0001866 || MONDO:0021211"},{"label":"bipolar I disorder || bulimia nervosa","ontology_term_id":"MONDO:0001866 || MONDO:0005452"},{"label":"bipolar I disorder || bulimia nervosa || obsessive-compulsive disorder","ontology_term_id":"MONDO:0001866 || MONDO:0005452 || MONDO:0008114"},{"label":"bipolar I disorder || obsessive-compulsive disorder","ontology_term_id":"MONDO:0001866 || MONDO:0008114"},{"label":"bipolar I disorder || post-traumatic stress disorder","ontology_term_id":"MONDO:0001866 || MONDO:0005146"},{"label":"bipolar I disorder || type 1 diabetes mellitus","ontology_term_id":"MONDO:0001866 || MONDO:0005147"},{"label":"bipolar I disorder || type 2 diabetes mellitus","ontology_term_id":"MONDO:0001866 || MONDO:0005148"},{"label":"bipolar II disorder","ontology_term_id":"MONDO:0000693"},{"label":"bipolar II disorder || type 1 diabetes 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Parkinson disease || progressive supranuclear palsy","ontology_term_id":"MONDO:0001627 || MONDO:0005180 || MONDO:0019037"},{"label":"dementia || amyotrophic lateral sclerosis","ontology_term_id":"MONDO:0001627 || MONDO:0004976"},{"label":"dementia || argyrophilic grain disease","ontology_term_id":"MONDO:0001627 || MONDO:0700351"},{"label":"dementia || brain neoplasm","ontology_term_id":"MONDO:0001627 || MONDO:0021211"},{"label":"dementia || frontotemporal dementia","ontology_term_id":"MONDO:0001627 || MONDO:0017276"},{"label":"dementia || head injury","ontology_term_id":"MONDO:0001627 || MONDO:0800482"},{"label":"dementia || major depressive disorder || Alzheimer disease || Lewy body dementia","ontology_term_id":"MONDO:0001627 || MONDO:0002009 || MONDO:0004975 || MONDO:0007488"},{"label":"dementia || multiple sclerosis","ontology_term_id":"MONDO:0001627 || MONDO:0005301"},{"label":"dementia || normal pressure hydrocephalus","ontology_term_id":"MONDO:0001627 || 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MONDO:0004648 || MONDO:0004975 || MONDO:0005090"},{"label":"dementia || vascular dementia || argyrophilic grain disease","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0700351"},{"label":"dementia || vascular dementia || head injury","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0800482"},{"label":"dementia || vascular dementia || schizophrenia","ontology_term_id":"MONDO:0001627 || MONDO:0004648 || MONDO:0005090"},{"label":"frontotemporal dementia","ontology_term_id":"MONDO:0017276"},{"label":"head injury","ontology_term_id":"MONDO:0800482"},{"label":"major depressive disorder || tauopathy","ontology_term_id":"MONDO:0002009 || MONDO:0005574"},{"label":"multiple sclerosis","ontology_term_id":"MONDO:0005301"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"normal pressure hydrocephalus","ontology_term_id":"MONDO:0009366"},{"label":"progressive supranuclear palsy","ontology_term_id":"MONDO:0019037"},{"label":"schizophrenia","ontology_term_id":"MONDO:0005090"},{"label":"schizophrenia || brain neoplasm","ontology_term_id":"MONDO:0005090 || MONDO:0021211"},{"label":"tauopathy","ontology_term_id":"MONDO:0005574"},{"label":"vascular dementia","ontology_term_id":"MONDO:0004648"},{"label":"vascular dementia || Lewy body dementia","ontology_term_id":"MONDO:0004648 || MONDO:0007488"},{"label":"vascular dementia || progressive supranuclear palsy","ontology_term_id":"MONDO:0004648 || MONDO:0019037"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dorsolateral prefrontal cortex","ontology_term_id":"UBERON:0009834","tissue_type":"tissue"}]}],"description":"Neurodegenerative diseases and serious mental illnesses often exhibit overlapping characteristics, highlighting the potential for shared underlying mechanisms. To facilitate a deeper understanding of these diseases and pave the way for more effective treatments, we have generated a population-scale multi-omics dataset consisting of genotype and single-nucleus transcriptome data from the prefrontal cortex of frozen human brain specimens. Encompassing over 6.3 million nuclei from 1,494 donors, our dataset represents a diverse range of neurodegenerative and serious mental illnesses, including Alzheimer's and Parkinson\u2019s diseases, schizophrenia, bipolar disorder and diffuse Lewy body dementia, as well as neurotypical controls. Notably, 48% of all donors displayed neuropsychiatric symptoms, while over 21% received multiple diagnoses. The dataset presents an unprecedented opportunity to investigate both common and distinct molecular pathways spanning a range of brain-related disorders. We have performed stringent preprocessing and quality controls, ensuring the reliability and usability of the data. As a commitment to fostering collaborative research, we provide this valuable resource as an online repository, enabling widespread analyses across the scientific community.","doi":"10.1101/2024.10.31.24316513","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/DiseaseNeuroGenomics/PsychADxD"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://adknowledgeportal.synapse.org/Explore/Studies/DetailsPage/StudyDetails?Study=syn52160016"},{"link_name":"","link_type":"OTHER","link_url":"https://psych-ad.org/"},{"link_name":"Yang et al. (2024) medRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2024.11.06.24316592"},{"link_name":"He et al. (2024) medRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2024.11.01.24316586"},{"link_name":"Chandrashekar et al. (2024) medRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2024.11.01.24316589"},{"link_name":"Zeng et al. (2024) medRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2024.11.02.24316590"},{"link_name":"Venkatesh et al. (2024) medRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2024.11.04.24316495"},{"link_name":"Hoffman et al. (2024) bioRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2025.01.29.635498"},{"link_name":"Ramaswamy et al. (2024) bioRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2023.05.19.541376"},{"link_name":"Hoffman et al. (2024) bioRxiv","link_type":"OTHER","link_url":"https://doi.org/10.1101/2023.03.17.533005"},{"link_name":"Fullard et al. (2025) Sci Data","link_type":"OTHER","link_url":"https://doi.org/10.1038/s41597-025-04687-5"}],"name":"Population-scale cross-disorder atlas of the human prefrontal cortex at single-cell resolution","published_at":"2025-07-29T00:57:06+00:00","publisher_metadata":{"authors":[{"family":"Lee","given":"Donghoon"},{"family":"Koutrouli","given":"Mikaela"},{"family":"Masse","given":"Nicolas Y."},{"family":"Hoffman","given":"Gabriel E."},{"family":"Kinrot","given":"Seon"},{"family":"Wang","given":"Xinyi"},{"family":"N.M.","given":"Prashant"},{"family":"Pjanic","given":"Milos"},{"family":"Clarence","given":"Tereza"},{"family":"Tsetsos","given":"Fotios"},{"family":"Mathur","given":"Deepika"},{"family":"Burstein","given":"David"},{"family":"Therrien","given":"Karen"},{"family":"Hong","given":"Aram"},{"family":"Casey","given":"Clara"},{"family":"Shao","given":"Zhiping"},{"family":"Alvia","given":"Marcela"},{"family":"Argyriou","given":"Stathis"},{"family":"Monteiro Fortes","given":"Jennifer"},{"family":"Katsel","given":"Pavel"},{"family":"Auluck","given":"Pavan K."},{"family":"Barnes","given":"Lisa L."},{"family":"Marenco","given":"Stefano"},{"family":"Bennett","given":"David A."},{"name":"PsychAD Consortium"},{"family":"Jensen","given":"Lars Juhl"},{"family":"Girdhar","given":"Kiran"},{"family":"Voloudakis","given":"Georgios"},{"family":"Haroutunian","given":"Vahram"},{"family":"Bendl","given":"Jaroslav"},{"family":"Fullard","given":"John F."},{"family":"Roussos","given":"Panos"}],"is_preprint":true,"journal":"medRxiv","published_at":1730678400.0,"published_day":4,"published_month":11,"published_year":2024},"revised_at":"2026-06-11T16:54:13+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5e143645-177c-45b6-952d-48770e29a54b","collection_url":"https://cellxgene.cziscience.com/collections/5e143645-177c-45b6-952d-48770e29a54b","collection_version_id":"aa0f3f48-80b0-4f75-93a4-ce9463037460","consortia":["Human Cell Atlas (HCA)"],"contact_email":"orr@broadinstitute.org","contact_name":"Orr Ashenberg","created_at":"2026-06-10T02:30:01+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"b0ef440b-e303-4ad2-ada8-ce13336280ba","dataset_version_id":"e046218f-6a66-46f9-a91c-7f26b4ee00c2","disease":[{"label":"atopic eczema","ontology_term_id":"MONDO:0004980"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"skin of body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"}]}],"description":"In atopic dermatitis (AD), skin barrier and immune dysfunction result in chronic tissue inflammation, yet our understanding of the tissue ecosystem remains incomplete. Here, we generate a multi-modal census of 280,518 cells from whole skin tissue samples from 17 adults, including 11 AD patients, integrating it with 430,186 cell profiles from four previous studies into a comprehensive human skin cell atlas. Reconstruction of keratinocyte differentiation revealed disrupted cornification in AD associated with signals from an immune and stromal multicellular community \u2013 comprising MMP12+ and migratory dendritic cells (DCs), cycling innate lymphoid cells (ILC), natural killer cells, inflammatory CCL19+ IL4I1+ fibroblasts, and clonally expanded IL13+IL22+IL26+ T cells connected by intercellular feedback loops predicted to impact community assembly. Subsets from this community, along with disrupted cornified keratinocytes, were enriched in GWAS, suggesting that dysfunction in this communication network may initiate AD. Our work highlights disease-associated cell subsets and interactions in chronic skin inflammation.","doi":"10.1038/s41467-026-69587-7","is_pre_analysis":false,"links":[{"link_name":"GSE204765","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE204765"},{"link_name":"phs004337.v1.p1","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs004337.v1.p1"}],"name":"Multi-modal skin atlas identifies a multicellular immune-stromal community associated with altered cornification and specific T cell expansion in atopic dermatitis","published_at":"2026-05-04T19:30:04+00:00","publisher_metadata":{"authors":[{"family":"Fiskin","given":"Evgenij"},{"family":"Eraslan","given":"G\u00f6kcen"},{"family":"Alora-Palli","given":"Maria B."},{"family":"Jain","given":"Tanvi"},{"family":"Leyva-Castillo","given":"Juan 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Commun","published_at":1771977600.0,"published_day":25,"published_month":2,"published_year":2026},"revised_at":"2026-06-11T16:53:22+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"613f5480-4957-4f80-b804-0e2b85ac454c","collection_url":"https://cellxgene.cziscience.com/collections/613f5480-4957-4f80-b804-0e2b85ac454c","collection_version_id":"ce2272eb-3dcc-4571-b7cc-1631a6e7365b","consortia":[],"contact_email":"gregor.andelfinger.med@ssss.gouv.qc.ca","contact_name":"Gregor Andelfinger","created_at":"2026-06-10T05:01:31+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"731e0ae7-e600-470f-a6dc-8c35c28d6c3d","dataset_version_id":"287a43aa-a1bd-41bd-925e-0ac43fdb1228","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus 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scRNA-seq","published_at":"2024-03-25T20:15:56+00:00","publisher_metadata":{"authors":[{"family":"Feulner","given":"Lara"},{"family":"W\u00fcnnemann","given":"Florian"},{"family":"Liang","given":"Jenna"},{"family":"Hofmann","given":"Philipp"},{"family":"Hitz","given":"Marc-Phillip"},{"family":"Schapiro","given":"Denis"},{"family":"Leclerc","given":"Severine"},{"family":"van Vliet","given":"Patrick Piet"},{"family":"Andelfinger","given":"Gregor"}],"is_preprint":true,"journal":"bioRxiv","published_at":1710028800.0,"published_day":10,"published_month":3,"published_year":2024},"revised_at":"2026-06-11T16:53:23+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ceb895f4-ff9f-403a-b7c3-187a9657ac2c","collection_url":"https://cellxgene.cziscience.com/collections/ceb895f4-ff9f-403a-b7c3-187a9657ac2c","collection_version_id":"cfbc8200-7225-4ca6-8f52-5d7d27696139","consortia":["BRAIN 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time-points from fetus to adult. Frozen human cortical brain specimens from the 6 developmental time points were homogenized and purified by FANS prior to tagmentation and partitioning into single nuclei. 8000 nuclei from each sample were subjected to the Chromium Next GEM Single Cell Multiome ATAC and Gene Expression protocol (10x Genomics), according to manufacturer\u2019s instructions. Resulting libraries were quantified using the KAPA library quantification kit (KAPA Biosystems) and fragment sizes determined by Tapestation (Agilent). All libraries were sequenced at New York Genome Center (NYGC) using the Novaseq platform (Illumina). Fastq alignment, filtering, barcode counting, peak calling and counting of both ATAC and gene expression molecules were performed with cellranger-arc (v.1.0.0). We processed the outputs of Cell Ranger ARC using Seurat v4.013 and Signac v1.1.045 to create a multi-omic Seurat object with paired gene expression and DNA accessibility profiles for each sample. For chromatin accessibility, we used MACS246 as implemented in the function CallPeaks in Signac to call peaks from the fragment files.","doi":"10.1126/sciadv.adg3754","is_pre_analysis":false,"links":[{"link_name":"SCP1859","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1859/multi-omic-profiling-of-the-developing-human-cerebral-cortex-at-the-single-cell-level#study-visualize"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://labs.icahn.mssm.edu/roussos-lab/3dg_dual_assay/"},{"link_name":"","link_type":"OTHER","link_url":"http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr19%3A35900492%2D35912218&hgsid=1668910814_ETDbYELJdXdAJxwH5B3WBAX4xLt6"},{"link_name":"GSE204684","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE204684"},{"link_name":"analysis code","link_type":"OTHER","link_url":"https://zenodo.org/records/7703253"}],"name":"Multi-omic profiling of the developing human cerebral cortex at the single cell level","published_at":"2023-08-28T17:56:54+00:00","publisher_metadata":{"authors":[{"family":"Zhu","given":"Kaiyi"},{"family":"Bendl","given":"Jaroslav"},{"family":"Rahman","given":"Samir"},{"family":"Vicari","given":"James M."},{"family":"Coleman","given":"Claire"},{"family":"Clarence","given":"Tereza"},{"family":"Latouche","given":"Ovaun"},{"family":"Tsankova","given":"Nadejda M."},{"family":"Li","given":"Aiqun"},{"family":"Brennand","given":"Kristen J."},{"family":"Lee","given":"Donghoon"},{"family":"Yuan","given":"Guo-Cheng"},{"family":"Fullard","given":"John F."},{"family":"Roussos","given":"Panos"}],"is_preprint":false,"journal":"Sci. 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We profiled \u223c1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures.","doi":"10.1016/j.cell.2021.04.021","is_pre_analysis":false,"links":[{"link_name":"Allen Brain Map (10x)","link_type":"DATA_SOURCE","link_url":"https://portal.brain-map.org/atlases-and-data/rnaseq/mouse-whole-cortex-and-hippocampus-10x"},{"link_name":"Allen Brain Map (SMART-seq)","link_type":"DATA_SOURCE","link_url":"https://portal.brain-map.org/atlases-and-data/rnaseq/mouse-whole-cortex-and-hippocampus-smart-seq"},{"link_name":"GSE185862","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185862"},{"link_name":"NeMo","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-jb2f34y"}],"name":"A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation","published_at":"2023-05-26T17:49:58+00:00","publisher_metadata":{"authors":[{"family":"Yao","given":"Zizhen"},{"family":"van Velthoven","given":"Cindy T.J."},{"family":"Nguyen","given":"Thuc Nghi"},{"family":"Goldy","given":"Jeff"},{"family":"Sedeno-Cortes","given":"Adriana E."},{"family":"Baftizadeh","given":"Fahimeh"},{"family":"Bertagnolli","given":"Darren"},{"family":"Casper","given":"Tamara"},{"family":"Chiang","given":"Megan"},{"family":"Crichton","given":"Kirsten"},{"family":"Ding","given":"Song-Lin"},{"family":"Fong","given":"Olivia"},{"family":"Garren","given":"Emma"},{"family":"Glandon","given":"Alexandra"},{"family":"Gouwens","given":"Nathan W."},{"family":"Gray","given":"James"},{"family":"Graybuck","given":"Lucas T."},{"family":"Hawrylycz","given":"Michael J."},{"family":"Hirschstein","given":"Daniel"},{"family":"Kroll","given":"Matthew"},{"family":"Lathia","given":"Kanan"},{"family":"Lee","given":"Changkyu"},{"family":"Levi","given":"Boaz"},{"family":"McMillen","given":"Delissa"},{"family":"Mok","given":"Stephanie"},{"family":"Pham","given":"Thanh"},{"family":"Ren","given":"Qingzhong"},{"family":"Rimorin","given":"Christine"},{"family":"Shapovalova","given":"Nadiya"},{"family":"Sulc","given":"Josef"},{"family":"Sunkin","given":"Susan M."},{"family":"Tieu","given":"Michael"},{"family":"Torkelson","given":"Amy"},{"family":"Tung","given":"Herman"},{"family":"Ward","given":"Katelyn"},{"family":"Dee","given":"Nick"},{"family":"Smith","given":"Kimberly A."},{"family":"Tasic","given":"Bosiljka"},{"family":"Zeng","given":"Hongkui"}],"is_preprint":false,"journal":"Cell","published_at":1622505600.0,"published_day":1,"published_month":6,"published_year":2021},"revised_at":"2026-06-11T16:54:18+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"16a4f6bc-2457-4e21-9b7a-9ba17c7b66c4","collection_url":"https://cellxgene.cziscience.com/collections/16a4f6bc-2457-4e21-9b7a-9ba17c7b66c4","collection_version_id":"0cd6da09-56db-478c-90c7-d8c54f64838b","consortia":[],"contact_email":"a.swarbrick@garvan.org.au","contact_name":"Alex Swarbrick","created_at":"2026-06-10T22:37:57+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"68b6114f-e990-4033-bfb3-c35536633aaa","dataset_version_id":"4d036b2c-6135-4515-9c44-a5aa7a2e32e5","disease":[{"label":"triple-negative breast carcinoma","ontology_term_id":"MONDO:0005494"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"mammary gland connective tissue","ontology_term_id":"UBERON:0003584","tissue_type":"tissue"}]}],"description":"The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple\u2010negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal\u2010targeted therapies. Single\u2010cell RNA sequencing of five TNBCs revealed two cancer\u2010associated fibroblast (CAF) and two perivascular\u2010like (PVL) subpopulations. CAFs clustered into two states: the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell signalling predictions, we provide evidence that stromal\u2010immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory\u2010CAFs and differentiated\u2010PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T\u2010cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.","doi":"10.15252/embj.2019104063","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1106/stromal-cell-diversity-associated-with-immune-evasion-in-human-triple-negative-breast-cancer#study-summary"},{"link_name":"EGAD00001006981","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001006981"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/sunnyzwu/stromal_subclasses"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://hexagon-saffron-p3ty.squarespace.com/data-and-code-access"}],"name":"Stromal cell diversity associated with immune evasion in human triple\u2010negative breast cancer","published_at":"2025-01-09T00:30:09+00:00","publisher_metadata":{"authors":[{"family":"Wu","given":"Sunny Z"},{"family":"Roden","given":"Daniel 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For coronal slices that cannot be registered to CCF, the rostral-caudal positions can be estimated by the intervals between slices (100\u00b5m for animal 1 and 200\u00b5m for animal 2). 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We performed single nucleus RNA (snRNA-seq) and assay for transposase accessible chromatin sequencing (snATAC-seq) on human kidney cortex from donors with and without diabetic kidney disease (DKD) to identify altered signaling pathways and transcription factors associated with DKD. Both snRNA-seq and snATAC-seq had an increased proportion of VCAM1+ injured proximal tubule cells (PT_VCAM1) in DKD samples. PT_VCAM1 has a pro-inflammatory expression signature and transcription factor motif enrichment implicated NFkB signaling. We used stratified linkage disequilibrium score regression to partition heritability of kidney-function-related traits using publicly-available GWAS summary statistics. Cell-specific PT_VCAM1 peaks were enriched for heritability of chronic kidney disease (CKD), suggesting that genetic background may regulate chromatin accessibility and DKD progression. snATAC-seq found cell-specific differentially accessible regions (DAR) throughout the nephron that change accessibility in DKD and these regions were enriched for glucocorticoid receptor (GR) motifs. Changes in chromatin accessibility were associated with decreased expression of insulin receptor, increased gluconeogenesis, and decreased expression of the GR cytosolic chaperone, FKBP5, in the diabetic proximal tubule. Cleavage under targets and release using nuclease (CUT&RUN) profiling of GR binding in bulk kidney cortex and an in vitro model of the proximal tubule (RPTEC) showed that DAR co-localize with GR binding sites. CRISPRi silencing of GR response elements (GRE) in the FKBP5 gene body reduced FKBP5 expression in RPTEC, suggesting that reduced FKBP5 chromatin accessibility in DKD may alter cellular response to GR. We developed an open-source tool for single cell allele specific analysis (SALSA) to model the effect of genetic background on gene expression. Heterozygous germline single nucleotide variants (SNV) in proximal tubule ATAC peaks were associated with allele-specific chromatin accessibility and differential expression of target genes within cis-coaccessibility networks. Partitioned heritability of proximal tubule ATAC peaks with a predicted allele-specific effect was enriched for eGFR, suggesting that genetic background may modify DKD progression in a cell-specific manner.","doi":"10.1038/s41467-022-32972-z","is_pre_analysis":false,"links":[{"link_name":"GSE195460","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE195460"},{"link_name":"GSE151302","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE151302"},{"link_name":"GSE131882","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131882"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://humphreyslab.com/SingleCell/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/p4rkerw/SALSA"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/p4rkerw/Wilson_Muto_NComm_2022"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/3d49e5e5-976f-44cb-b6b9-079016c31c56"}],"name":"Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression","published_at":"2023-03-22T22:18:51+00:00","publisher_metadata":{"authors":[{"family":"Wilson","given":"Parker C."},{"family":"Muto","given":"Yoshiharu"},{"family":"Wu","given":"Haojia"},{"family":"Karihaloo","given":"Anil"},{"family":"Waikar","given":"Sushrut S."},{"family":"Humphreys","given":"Benjamin D."}],"is_preprint":false,"journal":"Nat Commun","published_at":1662422400.0,"published_day":6,"published_month":9,"published_year":2022},"revised_at":"2026-06-11T16:53:27+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5542eeb0-96ef-4ab9-95ea-eb6abc178461","collection_url":"https://cellxgene.cziscience.com/collections/5542eeb0-96ef-4ab9-95ea-eb6abc178461","collection_version_id":"9c90751f-0486-4239-a18f-3237d3e0d58a","consortia":[],"contact_email":"liran.shlush@weizmann.ac.il","contact_name":"Liran Shlush","created_at":"2026-06-10T01:11:05+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d9f3a82c-24bb-4277-b715-8ec92a33dd32","dataset_version_id":"7cbae627-b2a7-4f72-ae28-49afaf35b7a7","disease":[{"label":"hematologic disorder","ontology_term_id":"MONDO:0005570"},{"label":"myelodysplastic syndrome","ontology_term_id":"MONDO:0018881"},{"label":"myelodysplastic/myeloproliferative disease","ontology_term_id":"MONDO:0020077"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"4a5b00e0-1ba3-4fd4-af89-d3512eb20720","dataset_version_id":"24402055-3e47-463a-a9b0-6e04edd04ae2","disease":[{"label":"hematologic disorder","ontology_term_id":"MONDO:0005570"},{"label":"myelodysplastic syndrome","ontology_term_id":"MONDO:0018881"},{"label":"myelodysplastic/myeloproliferative disease","ontology_term_id":"MONDO:0020077"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"With aging, deviation of human blood counts from their normal range accompanies the transition from health to hematological and other diseases. Hematopoietic stem and progenitor cells (HSPCs) deliver life-long multi-lineage output, but their variation across healthy humans and their diagnostic utility haven\u2019t been characterized. To address this, we introduce an HSPC reference model using single-cell profiling of circulating CD34+ cells (cHSPCs) from 148 healthy individuals. We characterize physiological cHSPC composition, link it with standard blood counts and show that the ratio between lymphoid and myeloid progenitors is decreased in ageing males. Using this new reference model, we develop sensitive tools which could be used for diagnostics of myelodysplastic syndrome (MDS) from peripheral blood without bone marrow analysis. Profiling cHSPC compositions leads to the discovery of new MDS subclasses, ranging in their lymphocyte, basophil and granulocyte progenitor frequencies. The data and methodologies presented herein highlight the role of reference modeling in promoting clinical applications of single-cell genomics in MDS and in the future for other diseases too.","doi":"10.1038/s41591-025-03716-5","is_pre_analysis":false,"links":[{"link_name":"GSE285943","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE285943"},{"link_name":"Metacells","link_type":"LAB_WEBSITE","link_url":"https://apps.tanaylab.com/MCV/blood_aging"},{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/tanaylab/metacells"}],"name":"Human circulating hematopoietic stem and progenitor cells in aging, cytopenia and MDS","published_at":"2025-01-23T20:52:09+00:00","publisher_metadata":{"authors":[{"family":"Furer","given":"N."},{"family":"Rappoport","given":"N."},{"family":"Milman","given":"O."},{"family":"Tavor","given":"S."},{"family":"Lifshitz","given":"A."},{"family":"Bercovich","given":"A."},{"family":"Ben-Kiki","given":"O."},{"family":"Danin","given":"A."},{"family":"Kedmi","given":"M."},{"family":"Shipony","given":"Z."},{"family":"Lipson","given":"D."},{"family":"Meiri","given":"E."},{"family":"Yanai","given":"G."},{"family":"Shapira","given":"S."},{"family":"Arber","given":"N."},{"family":"Berdichevsky","given":"S."},{"family":"Tyner","given":"J."},{"family":"Joshi","given":"S."},{"family":"Landau","given":"D."},{"family":"Ganesan","given":"S."},{"family":"Dusaj","given":"N."},{"family":"Chamely","given":"P."},{"family":"Kaushansky","given":"N."},{"family":"Chapal-Ilani","given":"N."},{"family":"Shamir","given":"R."},{"family":"Tanay","given":"A."},{"family":"Shlush","given":"L."}],"is_preprint":false,"journal":"Nat Med","published_at":1751328000.0,"published_day":1,"published_month":7,"published_year":2025},"revised_at":"2026-06-11T16:54:20+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"7855daa4-3f34-4aae-b65a-87720c02e7cd","collection_url":"https://cellxgene.cziscience.com/collections/7855daa4-3f34-4aae-b65a-87720c02e7cd","collection_version_id":"61809737-f4ce-4a8d-aef9-fe72028a25ab","consortia":["CZI Cell Science"],"contact_email":"sanesj@mcb.harvard.edu","contact_name":"Joshua R. Sanes","created_at":"2026-06-10T00:50:07+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"9f1a899f-05a0-44c5-8aa9-39df61ae4324","dataset_version_id":"bcd39ae8-da6a-4c50-8764-057d54b3bc9c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cranial nerve II","ontology_term_id":"UBERON:0000941","tissue_type":"tissue"},{"label":"macula lutea","ontology_term_id":"UBERON:0000053","tissue_type":"tissue"},{"label":"optic disc","ontology_term_id":"UBERON:0001783","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"},{"label":"pigmented layer of retina","ontology_term_id":"UBERON:0001782","tissue_type":"tissue"},{"label":"sclera","ontology_term_id":"UBERON:0001773","tissue_type":"tissue"}]}],"description":"Although the visual system extends through the brain, most vision loss originates from defects in the eye. Its central element is the neural retina, which senses light, processes visual signals, and transmits them to the rest of the brain through the optic nerve (ON). Surrounding the retina are numerous other structures, conventionally divided into anterior and posterior segments. Here we used high-throughput single nucleus RNA sequencing (snRNA-seq) to classify and characterize cells in the extraretinal components of the posterior segment: ON, optic nerve head (ONH), peripheral sclera, peripapillary sclera (PPS), choroid, and retinal pigment epithelium (RPE). Defects in each of these tissues are associated with blinding diseases \u2013 for example, glaucoma (ONH and PPS), optic neuritis (ON), retinitis pigmentosa (RPE), and age-related macular degeneration (RPE and choroid). From \u223c151,000 single nuclei, we identified 37 transcriptomically distinct cell types, including multiple types of astrocytes, oligodendrocytes, fibroblasts, and vascular endothelial cells. Our analyses revealed a differential distribution of many cell types among distinct structures. Together with our previous analyses of the anterior segment and retina, the new data complete a \u201cVersion 1\u201d cell atlas of the human eye. We used this atlas to map the expression of >180 genes associated with the risk of developing glaucoma, which is known to involve ocular tissues in both anterior and posterior segments as well as neural retina. Similar methods can be used to investigate numerous additional ocular diseases, many of which are currently untreatable.","doi":"10.1073/pnas.2306153120","is_pre_analysis":false,"links":[{"link_name":"GSE236566","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?&acc=GSE236566"},{"link_name":"SCP2298","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP2298/transcriptomic-analysis-of-the-ocular-posterior-segment-completes-a-cell-atlas-of-the-human-eye"},{"link_name":"SCP2310","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP2310/transcriptomic-analysis-of-the-ocular-posterior-segment-completes-a-cell-atlas-of-the-human-eye-ocular-atlas"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/1c5eaabf-075b-4b7a-a9e6-07792c2034b3"}],"name":"Transcriptomic Analysis of the Ocular Posterior Segment Completes a Cell Atlas of the Human Eye","published_at":"2025-10-20T16:38:54+00:00","publisher_metadata":{"authors":[{"family":"Monavarfeshani","given":"Aboozar"},{"family":"Yan","given":"Wenjun"},{"family":"Pappas","given":"Christian"},{"family":"Odenigbo","given":"Kenechukwu A."},{"family":"He","given":"Zhigang"},{"family":"Segr\u00e8","given":"Ayellet V."},{"family":"van Zyl","given":"Tav\u00e9"},{"family":"Hageman","given":"Gregory S."},{"family":"Sanes","given":"Joshua R."}],"is_preprint":false,"journal":"Proc. Natl. Acad. Sci. U.S.A.","published_at":1692662400.0,"published_day":22,"published_month":8,"published_year":2023},"revised_at":"2026-06-11T16:53:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e2c257e7-6f79-487c-b81c-39451cd4ab3c","collection_url":"https://cellxgene.cziscience.com/collections/e2c257e7-6f79-487c-b81c-39451cd4ab3c","collection_version_id":"8c2f053f-b4fa-471b-b1f5-cd3e948ecdb8","consortia":["European Union\u2019s Horizon 2020","Wellcome HCA Strategic Science Support"],"contact_email":"rv4@sanger.ac.uk","contact_name":"Roser Vento-Tormo","created_at":"2026-06-10T02:31:49+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"Visium Spatial Gene Expression 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basalis","ontology_term_id":"UBERON:0000453","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"74cff64f-9da9-4b2a-9b3b-8a04a1598040","dataset_version_id":"7a4dd01b-96de-45cd-b4ac-c5892a8dc2bf","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"decidua","ontology_term_id":"UBERON:0002450","tissue_type":"tissue"},{"label":"decidua basalis","ontology_term_id":"UBERON:0000453","tissue_type":"tissue"},{"label":"placenta","ontology_term_id":"UBERON:0001987","tissue_type":"tissue"}]},{"assay":[{"label":"Visium Spatial Gene 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Extravillous trophoblast cells (EVTs) derived from placental villi infiltrate the decidua, transforming the maternal arteries into high-conductance vessels. Defects in trophoblast invasion and arterial transformation established during early pregnancy underlie common pregnancy disorders such as pre-eclampsia. Here we have generated a spatially resolved multiomics single-cell atlas of the entire human maternal\u2013fetal interface including the myometrium, which enables us to resolve the full trajectory of trophoblast differentiation. We have used this cellular map to infer the possible transcription factors mediating EVT invasion and show that they are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. We define the transcriptomes of the final cell states of trophoblast invasion: placental bed giant cells (fused multinucleated EVTs) and endovascular EVTs (which form plugs inside the maternal arteries). We predict the cell\u2013cell communication events contributing to trophoblast invasion and placental bed giant cell formation, and model the dual role of interstitial EVTs and endovascular EVTs in mediating arterial transformation during early pregnancy. Together, our data provide a comprehensive analysis of postimplantation trophoblast differentiation that can be used to inform the design of experimental models of the human placenta in early pregnancy.","doi":"10.1038/s41586-023-05869-0","is_pre_analysis":false,"links":[{"link_name":"Online web portal","link_type":"DATA_SOURCE","link_url":"https://www.reproductivecellatlas.org/mfi.html"},{"link_name":"scRNA-seq and snRNA-seq of primary tissue (E-MTAB-12421)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12421"},{"link_name":"multiome snRNA-seq and snATAC-seq (E-MTAB-12595)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12595"},{"link_name":"scRNA-seq and snRNA-seq of historical placental beds(EGAD00001010037)","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001010037"},{"link_name":"multiome snRNA-seq and snATAC-seq of historical placental beds(EGAD00001010038)","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001010038"},{"link_name":"scRNA-seq and snRNA-seq of TSCs(EGAD00001010017)","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001010017"},{"link_name":"Image datasets","link_type":"DATA_SOURCE","link_url":"https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BIAD615"},{"link_name":"scRNA-seq and snucRNA-seq of human primary trophoblast organoids (PTO) and trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs) (E-MTAB-12650)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12650"},{"link_name":"Spatial transcriptomics of human implantation sites, placenta and decidua (E-MTAB-12698)","link_type":"DATA_SOURCE","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12698"}],"name":"Spatial multiomics map of trophoblast development in early pregnancy","published_at":"2023-07-24T17:44:55+00:00","publisher_metadata":{"authors":[{"family":"Arutyunyan","given":"Anna"},{"family":"Roberts","given":"Kenny"},{"family":"Troul\u00e9","given":"Kevin"},{"family":"Wong","given":"Frederick C. K."},{"family":"Sheridan","given":"Megan A."},{"family":"Kats","given":"Ilia"},{"family":"Garcia-Alonso","given":"Luz"},{"family":"Velten","given":"Britta"},{"family":"Hoo","given":"Regina"},{"family":"Ruiz-Morales","given":"Elias R."},{"family":"Sancho-Serra","given":"Carmen"},{"family":"Shilts","given":"Jarrod"},{"family":"Handfield","given":"Louis-Francois"},{"family":"Marconato","given":"Luca"},{"family":"Tuck","given":"Elizabeth"},{"family":"Gardner","given":"Lucy"},{"family":"Mazzeo","given":"Cecilia Icoresi"},{"family":"Li","given":"Qian"},{"family":"Kelava","given":"Iva"},{"family":"Wright","given":"Gavin J."},{"family":"Prigmore","given":"Elena"},{"family":"Teichmann","given":"Sarah A."},{"family":"Bayraktar","given":"Omer Ali"},{"family":"Moffett","given":"Ashley"},{"family":"Stegle","given":"Oliver"},{"family":"Turco","given":"Margherita Y."},{"family":"Vento-Tormo","given":"Roser"}],"is_preprint":false,"journal":"Nature","published_at":1680739200.0,"published_day":6,"published_month":4,"published_year":2023},"revised_at":"2026-06-11T16:53:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"690fb28b-e364-4d3d-8934-bae50ae93857","collection_url":"https://cellxgene.cziscience.com/collections/690fb28b-e364-4d3d-8934-bae50ae93857","collection_version_id":"89f7da38-815d-4f41-9291-ddf903755c2b","consortia":[],"contact_email":"cotneyj@chop.edu","contact_name":"Justin Cotney","created_at":"2026-06-10T02:35:41+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"f9ef78fc-700f-4e97-8a4c-85df06a2c583","dataset_version_id":"4d76b7b4-4d67-4016-b881-ab86e7f4d7f5","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo 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Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development, profiling over 42,000 nuclei from craniofacial tissues of 24 embryos spanning six key time points during the embryonic period (4\u20138 post-conception weeks). This resource resolves the transcriptional dynamics of seven major cell types and uncovers distinct populations, including muscle progenitors and CNCCs. Comparative analyses with murine datasets reveal substantial conservation of major cell types, alongside species-specific differences in gene expression programs. CNCCs, which are crucial for craniofacial morphogenesis, exhibit the lowest marker gene conservation, underscoring their evolutionary plasticity. Spatial transcriptomics further localizes cell populations, providing a detailed view of their developmental roles and anatomical context. We also link these developmental processes to genetic variation, identifying cell type-specific enrichments for common variants associated with facial morphology and rare variants linked to orofacial clefts. Intriguingly, Neanderthal-introgressed sequences are enriched near genes with biased expression in cartilage and specialized ectodermal subtypes, suggesting their contribution to modern human craniofacial features. This atlas offers unprecedented insights into the cellular and genetic mechanisms shaping the human face, highlighting conserved and human-specific aspects of craniofacial biology. Our findings illuminate the developmental origins of craniofacial disorders, the genetic basis of facial variation, and the evolutionary legacy of ancient hominins. This work provides a foundational resource for exploring craniofacial biology, with implications for developmental genetics, evolutionary biology, and clinical research into congenital anomalies.","doi":"10.1038/s41467-026-70232-6","is_pre_analysis":false,"links":[{"link_name":"zenodo.org","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.5281/zenodo.14343226"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/cotneylab/craniofacial_snrna"},{"link_name":"Human snRNA","link_type":"RAW_DATA","link_url":"https://doi.org/10.25550/8D-2JQ0"},{"link_name":"Mouse snRNA","link_type":"RAW_DATA","link_url":"https://doi.org/10.25550/7N-54BY"}],"name":"Gene expression patterns of the developing human and mouse face at single cell resolution","published_at":"2026-01-08T18:09:23+00:00","publisher_metadata":{"authors":[{"family":"Khouri-Farah","given":"Nagham"},{"family":"Manchel","given":"Alexandra"},{"family":"Wentworth Winchester","given":"Emma"},{"family":"Schilder","given":"Brian M."},{"family":"Robinson","given":"Kelsey"},{"family":"Curtis","given":"Sarah W."},{"family":"Skene","given":"Nathan G."},{"family":"Leslie-Clarkson","given":"Elizabeth J."},{"family":"Cotney","given":"Justin"}],"is_preprint":false,"journal":"Nat Commun","published_at":1773014400.0,"published_day":9,"published_month":3,"published_year":2026},"revised_at":"2026-06-11T16:53:31+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2b02dff7-e427-4cdc-96fb-c0f354c099aa","collection_url":"https://cellxgene.cziscience.com/collections/2b02dff7-e427-4cdc-96fb-c0f354c099aa","collection_version_id":"e6f553ab-99e7-4daa-8ddd-3307911f0c89","consortia":[],"contact_email":"miriam.merad@mssm.edu","contact_name":"Miriam Merad","created_at":"2026-06-16T00:13:36+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"36c867a7-be10-4e69-9b39-5de12b0af6da","dataset_version_id":"def59402-ffde-4e48-a3eb-963d9666be53","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ileum lamina propria","ontology_term_id":"UBERON:8600035","tissue_type":"tissue"}]}],"description":"Clinical benefits of cytokine blockade in ileal Crohn\u2019s disease (iCD) are limited to a subset of patients. Here, we applied single-cell technologies to iCD lesions to address whether cellular heterogeneity contributes to treatment resistance. We found that a subset of patients expressed a unique cellular module in inflamed tissues that consisted of IgG plasma cells, inflammatory mononuclear phagocytes, activated T cells, and stromal cells, which we named the GIMATS module. Analysis of ligand-receptor interaction pairs identified a distinct network connectivity that likely drives the GIMATS module. Strikingly, the GIMATS module was also present in a subset of patients in four independent iCD cohorts (n = 441), and its presence at diagnosis correlated with failure to achieve durable corticosteroid-free remission upon anti-TNF therapy. These results emphasize the limitations of current diagnostic assays and the potential for single-cell mapping tools to identify novel biomarkers of treatment response and tailored therapeutic opportunities.","doi":"10.1016/j.cell.2019.08.008","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE134809"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/effiken/martin_et_al_cell_2019"},{"link_name":"","link_type":"OTHER","link_url":"https://scdissector.org/martin/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/504e0cee-1688-40fa-b936-361c4a831f87"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-CURD-46"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=human-ileum"}],"name":"Single-Cell Analysis of Crohn\u2019s Disease Lesions Identifies a Pathogenic Cellular Module Associated with Resistance to Anti-TNF Therapy","published_at":"2022-04-26T09:35:40+00:00","publisher_metadata":{"authors":[{"family":"Martin","given":"Jerome C."},{"family":"Chang","given":"Christie"},{"family":"Boschetti","given":"Gilles"},{"family":"Ungaro","given":"Ryan"},{"family":"Giri","given":"Mamta"},{"family":"Grout","given":"John A."},{"family":"Gettler","given":"Kyle"},{"family":"Chuang","given":"Ling-shiang"},{"family":"Nayar","given":"Shikha"},{"family":"Greenstein","given":"Alexander J."},{"family":"Dubinsky","given":"Marla"},{"family":"Walker","given":"Laura"},{"family":"Leader","given":"Andrew"},{"family":"Fine","given":"Jay S."},{"family":"Whitehurst","given":"Charles E."},{"family":"Mbow","given":"M Lamine"},{"family":"Kugathasan","given":"Subra"},{"family":"Denson","given":"Lee A."},{"family":"Hyams","given":"Jeffrey S."},{"family":"Friedman","given":"Joshua R."},{"family":"Desai","given":"Prerak T."},{"family":"Ko","given":"Huaibin M."},{"family":"Laface","given":"Ilaria"},{"family":"Akturk","given":"Guray"},{"family":"Schadt","given":"Eric E."},{"family":"Salmon","given":"Helene"},{"family":"Gnjatic","given":"Sacha"},{"family":"Rahman","given":"Adeeb H."},{"family":"Merad","given":"Miriam"},{"family":"Cho","given":"Judy H."},{"family":"Kenigsberg","given":"Ephraim"}],"is_preprint":false,"journal":"Cell","published_at":1567296000.0,"published_day":1,"published_month":9,"published_year":2019},"revised_at":"2026-06-16T14:18:31+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c353707f-09a4-4f12-92a0-cb741e57e5f0","collection_url":"https://cellxgene.cziscience.com/collections/c353707f-09a4-4f12-92a0-cb741e57e5f0","collection_version_id":"594eb19a-5e8b-43f5-8cd5-9d4d5e70a954","consortia":["Human Cell Atlas (HCA)"],"contact_email":"m.rodriguez@dkfz-heidelberg.de","contact_name":"Manuel Rodr\u00edguez-Paredes","created_at":"2026-06-10T03:10:14+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"124744b8-4681-474a-9894-683896122708","dataset_version_id":"1a6bbe2b-4eed-477a-97c9-f7a74d4874d7","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"zone of skin","ontology_term_id":"UBERON:0000014","tissue_type":"tissue"}]}],"description":"Fibroblasts are an essential cell population for human skin architecture and function. While fibroblast heterogeneity is well established, this phenomenon has not been analyzed systematically yet. We have used single-cell RNA sequencing to analyze the transcriptomes of more than 5,000 fibroblasts from a sun-protected area in healthy human donors. Our results define four main subpopulations that can be spatially localized and show differential secretory, mesenchymal and pro-inflammatory functional annotations. Importantly, we found that this fibroblast \u2018priming\u2019 becomes reduced with age. We also show that aging causes a substantial reduction in the predicted interactions between dermal fibroblasts and other skin cells, including undifferentiated keratinocytes at the dermal-epidermal junction. Our work thus provides evidence for a functional specialization of human dermal fibroblasts and identifies the partial loss of cellular identity as an important age-related change in the human dermis. These findings have important implications for understanding human skin aging and its associated phenotypes.","doi":"10.1038/s42003-020-0922-4","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg38&g=skinSoleBoldo&position=default"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/51f02950-ee25-4f4b-8d07-59aa99bb3498"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=aging-human-skin"},{"link_name":"GSE130973","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE130973"}],"name":"Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming","published_at":"2022-06-15T22:24:57+00:00","publisher_metadata":{"authors":[{"family":"Sol\u00e9-Boldo","given":"Lloren\u00e7"},{"family":"Raddatz","given":"G\u00fcnter"},{"family":"Sch\u00fctz","given":"Sabrina"},{"family":"Mallm","given":"Jan-Philipp"},{"family":"Rippe","given":"Karsten"},{"family":"Lonsdorf","given":"Anke S."},{"family":"Rodr\u00edguez-Paredes","given":"Manuel"},{"family":"Lyko","given":"Frank"}],"is_preprint":false,"journal":"Commun Biol","published_day":1,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:54:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4fa07e63-f712-4d8c-b885-2c515b5e2743","collection_url":"https://cellxgene.cziscience.com/collections/4fa07e63-f712-4d8c-b885-2c515b5e2743","collection_version_id":"98e5d0f0-664a-4a05-8692-326a2f60f04c","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. 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patch","ontology_term_id":"UBERON:0003454","tissue_type":"tissue"}]}],"description":"The intestinal immune system is highly adapted to maintaining tolerance to the commensal microbiota and self-antigens while defending against invading pathogens1,2. Recognizing how the diverse network of local cells establish homeostasis and maintains it in the complex immune environment of the gut is critical to understanding how tolerance can be re-established following dysfunction, such as in inflammatory disorders. Although cell and molecular interactions that control T regulatory (Treg) cell development and function have been identified3,4, less is known about the cellular neighbourhoods and spatial compartmentalization that shapes microorganism-reactive Treg cell function. Here we used in vivo live imaging, photo-activation-guided single-cell RNA sequencing5,6,7 and spatial transcriptomics to follow the natural history of T cells that are reactive towards Helicobacter hepaticus through space and time in the settings of tolerance and inflammation. Although antigen stimulation can occur anywhere in the tissue, the lamina propria\u2014but not embedded lymphoid aggregates\u2014is the key microniche that supports effector Treg (eTreg) cell function. eTreg cells are stable once their niche is established; however, unleashing inflammation breaks down compartmentalization, leading to dominance of CD103+SIRP\u03b1+ dendritic cells in the lamina propria. We identify and validate the putative tolerogenic interaction between CD206+ macrophages and eTreg cells in the lamina propria and identify receptor\u2013ligand pairs that are likely to govern the interaction. Our results reveal a spatial mechanism of tolerance in the lamina propria and demonstrate how knowledge of local interactions may contribute to the next generation of tolerance-inducing therapies.","doi":"10.1038/s41586-024-07251-0","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://treg-gut-niches.cellgeni.sanger.ac.uk/"},{"link_name":"scRNA-seq, scTCR-seq and Visium data","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB57700"}],"name":"Immune microniches shape intestinal Treg function","published_at":"2024-07-24T17:32:36+00:00","publisher_metadata":{"authors":[{"family":"Gu","given":"Yisu"},{"family":"Bartolom\u00e9-Casado","given":"Raquel"},{"family":"Xu","given":"Chuan"},{"family":"Bertocchi","given":"Alice"},{"family":"Janney","given":"Alina"},{"family":"Heuberger","given":"Cornelia"},{"family":"Pearson","given":"Claire F."},{"family":"Teichmann","given":"Sarah A."},{"family":"Thornton","given":"Emily E."},{"family":"Powrie","given":"Fiona"}],"is_preprint":false,"journal":"Nature","published_at":1714003200.0,"published_day":25,"published_month":4,"published_year":2024},"revised_at":"2026-06-11T16:54:22+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a064d795-3b77-44ae-9fb5-beb57c567443","collection_url":"https://cellxgene.cziscience.com/collections/a064d795-3b77-44ae-9fb5-beb57c567443","collection_version_id":"62bf9bf8-2838-4965-a04f-f1ff09908864","consortia":[],"contact_email":"jose.ordovas-montanes@childrens.harvard.edu","contact_name":"Jose Ordovas-Montanes","created_at":"2026-06-10T01:56:48+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"6ceeaa86-9ceb-4582-b390-6d4dd6ff0572","dataset_version_id":"8cf9e6a2-5cd6-4d8e-95bd-b8c54d05e3f1","disease":[{"label":"digestive system disorder","ontology_term_id":"MONDO:0004335"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lamina propria of small intestine","ontology_term_id":"UBERON:0001238","tissue_type":"tissue"}]}],"description":"FGID samples from the paper \"Concerted changes in the pediatric single-cell intestinal ecosystem before and after anti-TNF blockade\". Crohn's disease is an inflammatory bowel disease (IBD) which most often presents with patchy lesions in the terminal ileum and colon and requires complex clinical care. Recent advances in the targeting of cytokines and leukocyte migration have greatly advanced treatment options, but most patients still relapse and inevitably progress. Although single-cell approaches are transforming our ability to understand the barrier tissue biology of inflammatory disease, comprehensive single-cell RNA-sequencing (scRNA-seq) atlases of IBD to date have largely sampled pre-treated patients with established disease. This has limited our understanding of which cell types, subsets, and states at diagnosis are predictive of disease severity and response to treatment. Here, through a combined clinical, flow cytometric, and scRNA-seq study, we profile diagnostic human biopsies from the terminal ileum of treatment-naive pediatric patients with Crohn's disease(pediCD; n=14) and from non-inflamed pediatric controls with functional gastrointestinal disorders (FGID;n=13). To fully resolve and annotate epithelial, stromal, and immune cell states among the our 201,883 single-cell transcriptomes, we develop and deploy a principled and unbiased tiered clustering approach, ARBOL, yielding 138 FGID and 305 pediCD end cell clusters. Notably, through both flow cytometry and scRNA-seq, we observe that at the level of broad cell types, treatment-naive pediCD is not readily distinguishable from FGID in cellular composition. However, by integrating high-resolution scRNA-seq analysis, we identify significant differences in cell states that arise during pediCD relative to FGID. Furthermore, by closely linking our scRNA-seq analysis with clinical meta-data, we resolve a vector of lymphoid, myeloid, and epithelial cell states in treatment-naive samples which can distinguish patients with less severe disease (those not on anti-TNF therapies (NOA)), from those with more severe disease at presentation who require anti-TNF therapies.Moreover, this vector was also able to distinguish those patients that achieve a full response (FR) to anti-TNF blockade from those more treatment-resistant patients who only achieve a partial response (PR). Our study jointly leverages a treatment-naive cohort, high-resolution principled scRNA-seq data analysis, and clinical outcomes to understand which baseline cell states may predict inflammatory disease trajectory.","doi":"10.1101/2021.09.17.21263540","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1422/predict-2021-paper-fgid"}],"name":"Pediatric FGID lamina propria of ileum biopsies.","published_at":"2023-08-22T17:59:21+00:00","publisher_metadata":{"authors":[{"family":"Zheng","given":"Hengqi Betty"},{"family":"Doran","given":"Benjamin A."},{"family":"Kimler","given":"Kyle"},{"family":"Yu","given":"Alison"},{"family":"Tkachev","given":"Victor"},{"family":"Niederlova","given":"Veronika"},{"family":"Cribbin","given":"Kayla"},{"family":"Fleming","given":"Ryan"},{"family":"Bratrude","given":"Brandi"},{"family":"Betz","given":"Kayla"},{"family":"Cagnin","given":"Lorenzo"},{"family":"McGuckin","given":"Connor"},{"family":"Keskula","given":"Paula"},{"family":"Albanese","given":"Alexandre"},{"family":"Sacta","given":"Maria"},{"family":"de Sousa Casal","given":"Joshua"},{"family":"van Esch","given":"Ruben"},{"family":"Kwong","given":"Andrew C."},{"family":"Kummerlowe","given":"Conner"},{"family":"Taliaferro","given":"Faith"},{"family":"Fiaschi","given":"Nathalie"},{"family":"Kou","given":"Baijun"},{"family":"Coetzee","given":"Sandra"},{"family":"Jalal","given":"Sumreen"},{"family":"Yabe","given":"Yoko"},{"family":"Dobosz","given":"Michael"},{"family":"Wipperman","given":"Matthew F."},{"family":"Hamon","given":"Sara"},{"family":"Kalliolias","given":"George D."},{"family":"Hooper","given":"Andrea"},{"family":"Lim","given":"Wei Keat"},{"family":"Haxhinasto","given":"Sokol"},{"family":"Wei","given":"Yi"},{"family":"Ford","given":"Madeline"},{"family":"Ambartsumyan","given":"Lusine"},{"family":"Suskind","given":"David L."},{"family":"Lee","given":"Dale"},{"family":"Deutsch","given":"Gail"},{"family":"Deng","given":"Xuemei"},{"family":"Collen","given":"Lauren V."},{"family":"Mitsialis","given":"Vanessa"},{"family":"Snapper","given":"Scott B."},{"family":"Wahbeh","given":"Ghassan"},{"family":"Shalek","given":"Alex K."},{"family":"Ordovas-Montanes","given":"Jose"},{"family":"Kean","given":"Leslie S."}],"is_preprint":true,"journal":"medRxiv","published_at":1632268800.0,"published_day":22,"published_month":9,"published_year":2021},"revised_at":"2026-06-11T16:54:22+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a18474f4-ff1e-4864-af69-270b956cee5b","collection_url":"https://cellxgene.cziscience.com/collections/a18474f4-ff1e-4864-af69-270b956cee5b","collection_version_id":"4eeb7b4a-70cf-4d8e-831c-a3e8b2866d2b","consortia":[],"contact_email":"karol.nowicki-osuch@dkfz-heidelberg.de","contact_name":"Karol Nowicki-Osuch","created_at":"2026-06-16T14:27:36+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"faed4f71-6b50-4fc7-bd1c-8f385dccfdce","dataset_version_id":"3e0b5d2e-65cb-4f27-9938-51195ef46cea","disease":[{"label":"Barrett esophagus","ontology_term_id":"MONDO:0013662"},{"label":"gastric intestinal 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We hypothesize that BE-IM and GIM follow parallel developmental trajectories in response to differing inflammatory insults. Here, we construct a single-cell RNA-seq atlas, supported by protein expression studies, of the entire gastrointestinal tract spanning physiologically normal and pathological states including: gastric metaplasia in the esophagus (E-GM), BE-IM, atrophic gastritis and GIM. We demonstrate that BE-IM and GIM share molecular features, and individual cells simultaneously possess transcriptional properties of gastric and intestinal epithelia, suggesting phenotypic mosaicism. Transcriptionally E-GM resembles atrophic gastritis; genetically, it is clonal and has a lower mutational burden than BE-IM. Finally, we show that GIM and BE-IM acquire a pro-tumorigenic, activated fibroblast microenvironment. These findings suggest that BE-IM and GIM can be considered molecularly similar entities in adjacent organs opening the path for shared detection and treatment strategies.","doi":"10.1158/2159-8290.cd-22-0824","is_pre_analysis":false,"links":[{"link_name":"EGAD00001010074","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001010074"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/karolno/BE-GIM_Comparison"}],"name":"Single-cell RNA sequencing unifies developmental programs of Esophageal and Gastric Intestinal Metaplasia","published_at":"2023-03-15T22:01:21+00:00","publisher_metadata":{"authors":[{"family":"Nowicki-Osuch","given":"Karol"},{"family":"Zhuang","given":"Lizhe"},{"family":"Cheung","given":"Tik Shing"},{"family":"Black","given":"Emily L."},{"family":"Masqu\u00e9-Soler","given":"Neus"},{"family":"Devonshire","given":"Ginny"},{"family":"Redmond","given":"Aisling M."},{"family":"Freeman","given":"Adam"},{"family":"di 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Finally, we leverage the depth and temporal resolution of these whole embryo snapshots, together with other published data, to construct and curate a rooted tree of cell type relationships that spans mouse development from zygote to pup. Throughout this tree, we systematically nominate sets of transcription factors (TFs) and other genes as candidate drivers of the in vivo differentiation of hundreds of mammalian cell types. Remarkably, the most dramatic shifts in transcriptional state are observed in a restricted set of cell types in the hours immediately following birth, and presumably underlie the massive changes in physiology that must accompany the successful transition of a placental mammal to extrauterine life.","doi":"10.1038/s41586-024-07069-w","is_pre_analysis":false,"links":[{"link_name":"GSE186069","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE186069"},{"link_name":"GSE228590","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE228590"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://omg.gs.washington.edu/"}],"name":"A single-cell transcriptional timelapse of mouse embryonic development, from gastrula to pup","published_at":"2024-03-11T16:31:31+00:00","publisher_metadata":{"authors":[{"family":"Qiu","given":"Chengxiang"},{"family":"Martin","given":"Beth K."},{"family":"Welsh","given":"Ian C."},{"family":"Daza","given":"Riza M."},{"family":"Le","given":"Truc-Mai"},{"family":"Huang","given":"Xingfan"},{"family":"Nichols","given":"Eva K."},{"family":"Taylor","given":"Megan L."},{"family":"Fulton","given":"Olivia"},{"family":"O\u2019Day","given":"Diana R."},{"family":"Gomes","given":"Anne Roshella"},{"family":"Ilcisin","given":"Saskia"},{"family":"Srivatsan","given":"Sanjay"},{"family":"Deng","given":"Xinxian"},{"family":"Disteche","given":"Christine M."},{"family":"Noble","given":"William Stafford"},{"family":"Hamazaki","given":"Nobuhiko"},{"family":"Moens","given":"Cecilia B."},{"family":"Kimelman","given":"David"},{"family":"Cao","given":"Junyue"},{"family":"Schier","given":"Alexander F."},{"family":"Spielmann","given":"Malte"},{"family":"Murray","given":"Stephen A."},{"family":"Trapnell","given":"Cole"},{"family":"Shendure","given":"Jay"}],"is_preprint":false,"journal":"Nature","published_at":1709164800.0,"published_day":29,"published_month":2,"published_year":2024},"revised_at":"2026-06-11T16:54:24+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4dca242c-d302-4dba-a68f-4c61e7bad553","collection_url":"https://cellxgene.cziscience.com/collections/4dca242c-d302-4dba-a68f-4c61e7bad553","collection_version_id":"052ed8c5-ecc3-40aa-a499-484e85083cb0","consortia":["Allen Institute for Brain Science","BRAIN Initiative"],"contact_email":"trygveb@alleninstitute.org","contact_name":"Trygve E. 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Only a few hundred genes showed human-specific patterning in all or specific cell types, and were significantly enriched near human accelerated regions (HARs) and conserved deletions (hCONDELS) and in cell adhesion and intercellular signaling pathways. These results suggest that relatively few cellular and molecular changes uniquely define adult human cortical structure, particularly by affecting circuit connectivity and glial cell function.","doi":"10.1126/science.ade9516","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/AllenInstitute/Great_Ape_MTG"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-net1412"}],"name":"Comparative transcriptomics reveals human-specific cortical features","published_at":"2023-10-20T17:46:30+00:00","publisher_metadata":{"authors":[{"family":"Jorstad","given":"Nikolas L."},{"family":"Song","given":"Janet H. 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Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.","doi":"10.1016/j.cell.2021.12.018","is_pre_analysis":false,"links":[{"link_name":"GSE192742","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE192742"},{"link_name":"","link_type":"OTHER","link_url":"https://livercellatlas.org/index.php"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/425c2759-db66-4c93-a358-a562c069b1f1"}],"name":"Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"420d0f5d-b7ba-4b1e-88d0-44e9f733febd","dataset_version_id":"25502281-532a-4a75-8188-d91d731659f2","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3cb646ab-d411-4e5b-89eb-082a786c953b","dataset_version_id":"f2b17940-46a7-4313-98d8-db8df78895bd","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0c0c49a2-b96b-432f-98a4-1decf9929149","dataset_version_id":"ef06a7c5-3e90-4c2a-80b3-b6d28287d11b","disease":[{"label":"cytomegalovirus infection","ontology_term_id":"MONDO:0005132"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0a8e3443-c3e2-4918-84db-0495657d9175","dataset_version_id":"4015a993-cac9-4732-94ff-74c48b37dc29","disease":[{"label":"cytomegalovirus infection","ontology_term_id":"MONDO:0005132"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"The generation and maintenance of immunity is a dynamic process that is dependent on age. Here, to better understand its progression, we profiled peripheral immunity in more than 300 healthy adults (25 to 90\u2009years of age) using single-cell RNA sequencing, proteomics and flow cytometry, following 96 adults longitudinally across 2 years with seasonal influenza vaccination. The resulting resource generated a single-cell RNA sequencing dataset of more than 16 million peripheral blood mononuclear cells with 71 immune cell subsets from our Human Immune Health Atlas and enabled us to interrogate how immune cell composition and states shift with age, chronic viral infection and vaccination. From these data, we demonstrate robust, non-linear transcriptional reprogramming in T cell subsets with age that is not driven by systemic inflammation or chronic cytomegalovirus infection. This age-related reprogramming led to a functional T helper 2 (TH2) cell bias in memory T cells that is linked to dysregulated B cell responses against highly boosted antigens in influenza vaccines. Collectively, this study reveals unique features of the immune ageing process that occur prior to advanced age and provides novel targets for age-related immune modulation. We provide interactive tools for exploring this extensive human immune health resource at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/.","doi":"10.1038/s41586-025-09686-5","is_pre_analysis":false,"links":[{"link_name":"Dynamics of IHA: scRNA-seq dataset github","link_type":"OTHER","link_url":"https://github.com/aifimmunology/sound-life-scrna-analysis/"},{"link_name":"Dynamics of IHA: Figures github","link_type":"OTHER","link_url":"https://github.com/aifimmunology/IHA-Figure"},{"link_name":"Dynamics of Human Immune Health and Age","link_type":"OTHER","link_url":"https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/"},{"link_name":"Human Immune Health Atlas Collection","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/77f9d7e9-5675-49c3-abed-ce02f39eef1b"},{"link_name":"GSE271896","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE271896"},{"link_name":"phs003841","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003841"}],"name":"Multi-omic profiling reveals age-related immune dynamics in healthy adults","published_at":"2025-10-24T23:35:56+00:00","publisher_metadata":{"authors":[{"family":"Gong","given":"Qiuyu"},{"family":"Sharma","given":"Mehul"},{"family":"Glass","given":"Marla C."},{"family":"Kuan","given":"Emma L."},{"family":"Chander","given":"Aishwarya"},{"family":"Singh","given":"Mansi"},{"family":"Graybuck","given":"Lucas T."},{"family":"Thomson","given":"Zachary J."},{"family":"LaFrance","given":"Christian M."},{"family":"Rachid Zaim","given":"Samir"},{"family":"Peng","given":"Tao"},{"family":"Okada","given":"Lauren Y."},{"family":"Genge","given":"Palak C."},{"family":"Henderson","given":"Katherine E."},{"family":"Dornisch","given":"Elisabeth M."},{"family":"Layton","given":"Erik D."},{"family":"Wittig","given":"Peter J."},{"family":"Heubeck","given":"Alexander T."},{"family":"Mukuka","given":"Nelson M."},{"family":"Reading","given":"Julian"},{"family":"Strawn","given":"Garrett"},{"family":"Titus-Adewunmi","given":"Teminijesu"},{"family":"Abadie","given":"Kathleen"},{"family":"Roll","given":"Charles R."},{"family":"Hernandez","given":"Veronica"},{"family":"Parthasarathy","given":"Vaishnavi"},{"family":"Stuckey","given":"Tyanna J."},{"family":"Musgrove","given":"Blessing"},{"family":"Swanson","given":"Elliott"},{"family":"Lord","given":"Cara"},{"family":"Weiss","given":"Morgan D. A."},{"family":"Phalen","given":"Cole G."},{"family":"Mettey","given":"Regina R."},{"family":"Lee","given":"Kevin J."},{"family":"Johanneson","given":"John B."},{"family":"Kawelo","given":"Erin K."},{"family":"Garber","given":"Jessica"},{"family":"Krishnan","given":"Upaasana"},{"family":"Smithmyer","given":"Megan"},{"family":"Wherry","given":"E. John"},{"family":"Vella","given":"Laura A."},{"family":"Henrickson","given":"Sarah E."},{"family":"Kopp","given":"Mackenzie S."},{"family":"Savage","given":"Adam K."},{"family":"Becker","given":"Lynne A."},{"family":"Meijer","given":"Paul"},{"family":"Coffey","given":"Ernest M."},{"family":"Goronzy","given":"Jorg J."},{"family":"Sigvardsson","given":"Mikael"},{"family":"Speake","given":"Cate"},{"family":"Bumol","given":"Thomas F."},{"family":"Goldrath","given":"Ananda W."},{"family":"Torgerson","given":"Troy R."},{"family":"Li","given":"Xiao-jun"},{"family":"Skene","given":"Peter J."},{"family":"Buckner","given":"Jane H."},{"family":"Gustafson","given":"Claire E."}],"is_preprint":false,"journal":"Nature","published_at":1766016000.0,"published_day":18,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:53:28+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"348da6dc-5bf6-435d-adc5-37747b9ae38a","collection_url":"https://cellxgene.cziscience.com/collections/348da6dc-5bf6-435d-adc5-37747b9ae38a","collection_version_id":"5c9b5ef0-e3d9-4277-89dc-cbc9973de5a5","consortia":[],"contact_email":"howchang@stanford.edu","contact_name":"Howard Y. Chang","created_at":"2026-06-10T05:07:29+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"322c816f-608a-4da1-99c4-36ca4ad45146","dataset_version_id":"74ec3a77-f1ff-4e90-af45-b8937cea0a8f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"retina","ontology_term_id":"UBERON:0000966","tissue_type":"tissue"}]}],"description":"Genome-wide association studies (GWASs) of eye disorders have identified hundreds of genetic variants associated with ocular disease. However, the vast majority of these variants are noncoding, making it challenging to interpret their function. Here we present a joint single-cell atlas of gene expression and chromatin accessibility of the adult human retina with more than 50,000 cells, which we used to analyze single-nucleotide polymorphisms (SNPs) implicated by GWASs of age-related macular degeneration, glaucoma, diabetic retinopathy, myopia, and type 2 macular telangiectasia. We integrate this atlas with a HiChIP enhancer connectome, expression quantitative trait loci (eQTL) data, and base-resolution deep learning models to predict noncoding SNPs with causal roles in eye disease, assess SNP impact on transcription factor binding, and define their known and novel target genes. Our efforts nominate pathogenic SNP-target gene interactions for multiple vision disorders and provide a potentially powerful resource for interpreting noncoding variation in the eye.","doi":"10.1016/j.xgen.2022.100164","is_pre_analysis":false,"links":[{"link_name":"SCP","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1755/joint-scrna-seq-and-scatac-seq-atlas-of-the-adult-human-retina#study-download"},{"link_name":"GSE196235","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196235"},{"link_name":"Data summary page","link_type":"OTHER","link_url":"https://eyemultiome.su.domains/"},{"link_name":"Analysis code","link_type":"PROTOCOL","link_url":"https://zenodo.org/record/6795162#.Y_bNQ-zMI0Q"},{"link_name":"BPNet Model Training","link_type":"PROTOCOL","link_url":"https://zenodo.org/record/6796067#.Y_bNaOzMI0Q"},{"link_name":"BPNet Models","link_type":"PROTOCOL","link_url":"https://zenodo.org/record/6330053#.Y_bNmOzMI0Q"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/4f4f0193-ede8-4a82-8cb0-7a0a22f06e63"}],"name":"Single-cell multiome of the human retina and deep learning nominate causal variants in complex eye diseases","published_at":"2023-03-01T20:26:25+00:00","publisher_metadata":{"authors":[{"family":"Wang","given":"Sean K."},{"family":"Nair","given":"Surag"},{"family":"Li","given":"Rui"},{"family":"Kraft","given":"Katerina"},{"family":"Pampari","given":"Anusri"},{"family":"Patel","given":"Aman"},{"family":"Kang","given":"Joyce B."},{"family":"Luong","given":"Christy"},{"family":"Kundaje","given":"Anshul"},{"family":"Chang","given":"Howard Y."}],"is_preprint":false,"journal":"Cell Genomics","published_at":1659312000.0,"published_day":1,"published_month":8,"published_year":2022},"revised_at":"2026-06-11T16:53:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e2a4a67f-6a18-431a-ab9c-6e77dd31cc80","collection_url":"https://cellxgene.cziscience.com/collections/e2a4a67f-6a18-431a-ab9c-6e77dd31cc80","collection_version_id":"15600fe6-7d7a-4e3a-9fb1-5ef39007dc41","consortia":["GenitoUrinary Development Molecular Anatomy Project (GUDMAP)"],"contact_email":"Douglas.Strand@UTSouthwestern.edu","contact_name":"Douglas Strand","created_at":"2026-06-10T00:46:49+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"ea426edb-4e86-4c53-ab17-5b952d94a31e","dataset_version_id":"3a1a0735-553a-47f6-948f-72cea750742f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"peripheral zone of prostate","ontology_term_id":"UBERON:8410026","tissue_type":"tissue"},{"label":"transition zone of prostate","ontology_term_id":"UBERON:8410025","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"e2a3c32d-71e2-4f38-b19c-dfcb8729cf46","dataset_version_id":"5f504bb1-30d6-471c-a666-0ceda60177be","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"peripheral zone of prostate","ontology_term_id":"UBERON:8410026","tissue_type":"tissue"},{"label":"transition zone of prostate","ontology_term_id":"UBERON:8410025","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"c3fe3c1e-5bf8-4678-b74a-79899243ad41","dataset_version_id":"13907b46-3c3c-4092-bb6d-7b3cdb0cf7a6","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"peripheral zone of prostate","ontology_term_id":"UBERON:8410026","tissue_type":"tissue"},{"label":"transition zone of prostate","ontology_term_id":"UBERON:8410025","tissue_type":"tissue"}]}],"description":"A comprehensive cellular anatomy of normal human prostate is essential for solving the cellular origins of benign prostatic hyperplasia and prostate cancer. The tools used to analyze the contribution of individual cell types are not robust. We provide a cellular atlas of the young adult human prostate and prostatic urethra using an iterative process of single-cell RNA sequencing (scRNA-seq) and flow cytometry on \u223c98,000 cells taken from different anatomical regions. Immunohistochemistry with newly derived cell type-specific markers revealed the distribution of each epithelial and stromal cell type on whole mounts, revising our understanding of zonal anatomy. Based on discovered cell surface markers, flow cytometry antibody panels were designed to improve the purification of each cell type, with each gate confirmed by scRNA-seq. The molecular classification, anatomical distribution, and purification tools for each cell type in the human prostate create a powerful resource for experimental design in human prostate disease.","doi":"10.1016/j.celrep.2018.11.086","is_pre_analysis":false,"links":[{"link_name":"www.gudmap.org","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.25548/W-R8CM"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=prostate-prostatic-urethra"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117403"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://strandlab.net/"},{"link_name":"","link_type":"OTHER","link_url":"https://git.biohpc.swmed.edu/StrandLab/sc-TissueMapper_Pr"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/53c53cd4-8127-4e12-bc7f-8fe1610a715c"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120716"}],"name":"A Cellular Anatomy of the Normal Adult Human Prostate and Prostatic Urethra","published_at":"2021-06-29T16:14:55+00:00","publisher_metadata":{"authors":[{"family":"Henry","given":"Gervaise H."},{"family":"Malewska","given":"Alicia"},{"family":"Joseph","given":"Diya B."},{"family":"Malladi","given":"Venkat S."},{"family":"Lee","given":"Jeon"},{"family":"Torrealba","given":"Jose"},{"family":"Mauck","given":"Ryan J."},{"family":"Gahan","given":"Jeffrey C."},{"family":"Raj","given":"Ganesh V."},{"family":"Roehrborn","given":"Claus G."},{"family":"Hon","given":"Gary C."},{"family":"MacConmara","given":"Malcolm P."},{"family":"Reese","given":"Jeffrey C."},{"family":"Hutchinson","given":"Ryan C."},{"family":"Vezina","given":"Chad M."},{"family":"Strand","given":"Douglas W."}],"is_preprint":false,"journal":"Cell Reports","published_at":1543622400.0,"published_day":1,"published_month":12,"published_year":2018},"revised_at":"2026-06-11T16:53:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"131c68c1-c457-4e3b-88bc-92c4e43ed680","collection_url":"https://cellxgene.cziscience.com/collections/131c68c1-c457-4e3b-88bc-92c4e43ed680","collection_version_id":"ad4a2ce6-dc94-4285-80ee-e390868c3b81","consortia":["CZI Cell Science"],"contact_email":"calliope.dendrou@kennedy.ox.ac.uk","contact_name":"Calliope Dendrou","created_at":"2026-06-16T16:58:17+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"b58c19c6-bc2d-4461-b9bf-60fa2ac91479","dataset_version_id":"d89e5a47-adb7-454a-b654-c3eeabdc57c3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"axillary lymph node","ontology_term_id":"UBERON:0001097","tissue_type":"tissue"}]}],"description":"Background: Early in vivo dynamics of human immune-cell activation across regionally activated lymphoid tissue sites upon immunisation are poorly characterised in ancestrally-diverse individuals with consequences for pandemic preparedness.\nMethods: In this experimental medicine study, draining and non-draining lymph nodes (dLNs and ndLNs) were studied by ultrasound (US)-guided fine-needle aspiration (FNA) in 13 adults aged 18-55 years with African and Asian ancestry, before and after receiving adjuvanted seasonal influenza vaccine (aQIV). A multi-modal investigation of ultrasound data, genotyping, systems serology, and single-cell multi-omics was undertaken.\nFindings: HLA subtypes reflected self-declared ethnicity and included 13 rarely described HLA-B alleles. Draining but not ndLNs rapidly increased in size post-vaccination, by day 3, with distinct cellular dynamics culminating in a cross-protective serological response. Dissecting LN cellular diversity into 42 lymphoid and non-lymphoid cell states, early post-vaccination cell abundance changes were observed across all LNs, but dLNs were characterised by CD4+ T follicular helper (CD4+ Tfh) cell expansion. Gene expression analysis revealed a dLN post-vaccination hub defined by CD4+ Tfh signalling, cross-compartmental activation, translation, and enhanced antigen-presentation capacity.\nInterpretation: Early CD4+ Tfh coordination in draining lymphoid tissue underpins robust responses to adjuvanted influenza vaccine that transcend ancestral inter-individual variation in young adults, with implications for vaccine design in ancestrally-diverse populations.","doi":"10.1016/j.ebiom.2025.106036","is_pre_analysis":false,"links":[{"link_name":"Zenodo code","link_type":"OTHER","link_url":"https://zenodo.org/records/15783553"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/6e465c30-1109-4c16-9fd5-deca9f9a05eb"}],"name":"Early lymph node T follicular helper cell signalling hub drives influenza vaccine response in an ancestrally diverse cohort","published_at":"2025-12-01T17:27:51+00:00","publisher_metadata":{"authors":[{"family":"Siu","given":"Jacqueline H.Y."},{"family":"Coelho","given":"Sofia"},{"family":"Palomeras","given":"Aime"},{"family":"Belij-Rammerstorfer","given":"Sandra"},{"family":"Barman","given":"Ninisha"},{"family":"Lee","given":"Chloe H."},{"family":"Str\u00f6bel","given":"Tamara"},{"family":"Thorpe","given":"Christopher J."},{"family":"Kaur","given":"Charandeep"},{"family":"Cole","given":"Tom"},{"family":"Remmert","given":"Nico"},{"family":"Fowler","given":"Jamie"},{"family":"Pledger","given":"Sam"},{"family":"Dooley","given":"Kyla B."},{"family":"Chan","given":"Terrence"},{"family":"H\u00f6schler","given":"Katja"},{"family":"Zambon","given":"Maria"},{"family":"Opoka","given":"Daniel"},{"family":"Szommer","given":"Tamas"},{"family":"Kim","given":"Seung J."},{"family":"Kumar","given":"Vinod"},{"family":"Vanderslott","given":"Samantha"},{"family":"Kaleebu","given":"Pontiano"},{"family":"Milicic","given":"Anita"},{"family":"Palmer","given":"Donald B."},{"family":"Lambe","given":"Teresa"},{"family":"Marsden","given":"Brian D."},{"family":"Koohy","given":"Hashem"},{"family":"Coles","given":"Mark"},{"family":"Dendrou","given":"Calliope A."},{"family":"Pollock","given":"Katrina M."}],"is_preprint":false,"journal":"eBioMedicine","published_at":1764547200.0,"published_day":1,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:53:36+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"436154da-bcf1-4130-9c8b-120ff9a888f2","collection_url":"https://cellxgene.cziscience.com/collections/436154da-bcf1-4130-9c8b-120ff9a888f2","collection_version_id":"0340d8f6-a8ca-4ad8-8664-07338a8bf55f","consortia":["CZI Cell Science"],"contact_email":"jimmie.ye@ucsf.edu","contact_name":"Chun Jimmie Ye","created_at":"2026-06-10T04:49:19+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"218acb0f-9f2f-4f76-b90b-15a4b7c7f629","dataset_version_id":"c55dc602-d168-4d15-acc1-5de4f2f5d551","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"systemic lupus erythematosus","ontology_term_id":"MONDO:0007915"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (162 cases, 99 controls) with multiplexed single-cell RNA-sequencing (mux-seq). Cases exhibited elevated expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of na\u00efve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data to map cell-type-specific cis-eQTLs and link SLE-associated variants to cell-type-specific expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.","doi":"10.1126/science.abf1970","is_pre_analysis":false,"links":[{"link_name":"phs002812","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002812"},{"link_name":"GSE137029","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137029"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/9fc0064b-84ce-40a5-a768-e6eb3d364ee0"},{"link_name":"Figure code","link_type":"OTHER","link_url":"https://zenodo.org/record/4724043#.YYQZDr3MKS5"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=lupus-pbmc"}],"name":"Single-cell RNA-seq reveals the cell-type-specific molecular and genetic associations to lupus","published_at":"2021-11-19T20:09:35+00:00","publisher_metadata":{"authors":[{"family":"Perez","given":"Richard K."},{"family":"Gordon","given":"M. 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To understand these dependencies within the wider microenvironment, we studied over 270,000 single-cell transcriptomes and 100 microdissected whole exomes from 12 patients with kidney tumors, prior to validation using spatial transcriptomics. Tissues were sampled from multiple regions of the tumor core, the tumor-normal interface, normal surrounding tissues, and peripheral blood. We find that the tissue-type location of CD8+ T cell clonotypes largely defines their exhaustion state with intra-tumoral spatial heterogeneity that is not well explained by somatic heterogeneity. De novo mutation calling from single-cell RNA-sequencing data allows us to broadly infer the clonality of stromal cells and lineage-trace myeloid cell development. We report six conserved meta-programs that distinguish tumor cell function, and find an epithelial-mesenchymal transition meta-program highly enriched at the tumor-normal interface that co-localizes with IL1B-expressing macrophages, offering a potential therapeutic target.","doi":"10.1016/j.ccell.2022.11.001","is_pre_analysis":false,"links":[{"link_name":"Single cell RNA sequencing and spatial transcriptomics data","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.17632/g67bkbnhhg.1"},{"link_name":"Single cell RNA sequencing data (EGAD00001008030)","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001008030"},{"link_name":"Spatial transcriptomic data (EGAD00001008781)","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001008781"},{"link_name":"Code and pipeline for deSCeRNAmut","link_type":"OTHER","link_url":"https://github.com/ThomasJamesMitchell/deSCeRNAMut"},{"link_name":"Online web portal","link_type":"DATA_SOURCE","link_url":"https://www.sanger.ac.uk/project/microenvironment-of-kidney-cancer"},{"link_name":"Analysis scripts","link_type":"OTHER","link_url":"https://github.com/ruoyan-li/RCC-spatial-mapping"},{"link_name":"","link_type":"OTHER","link_url":"https://data.humancellatlas.org/explore/projects/8f1f653d-3ea1-4d8e-b4a7-b97dc852c2b1"}],"name":"Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer","published_at":"2023-07-18T15:30:52+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Ruoyan"},{"family":"Ferdinand","given":"John R."},{"family":"Loudon","given":"Kevin W."},{"family":"Bowyer","given":"Georgina S."},{"family":"Laidlaw","given":"Sean"},{"family":"Muyas","given":"Francesc"},{"family":"Mamanova","given":"Lira"},{"family":"Neves","given":"Joana B."},{"family":"Bolt","given":"Liam"},{"family":"Fasouli","given":"Eirini S."},{"family":"Lawson","given":"Andrew R.J."},{"family":"Young","given":"Matthew D."},{"family":"Hooks","given":"Yvette"},{"family":"Oliver","given":"Thomas R.W."},{"family":"Butler","given":"Timothy M."},{"family":"Armitage","given":"James N."},{"family":"Aho","given":"Tev"},{"family":"Riddick","given":"Antony C.P."},{"family":"Gnanapragasam","given":"Vincent"},{"family":"Welsh","given":"Sarah J."},{"family":"Meyer","given":"Kerstin B."},{"family":"Warren","given":"Anne Y."},{"family":"Tran","given":"Maxine G.B."},{"family":"Stewart","given":"Grant D."},{"family":"Cort\u00e9s-Ciriano","given":"Isidro"},{"family":"Behjati","given":"Sam"},{"family":"Clatworthy","given":"Menna R."},{"family":"Campbell","given":"Peter J."},{"family":"Teichmann","given":"Sarah A."},{"family":"Mitchell","given":"Thomas J."}],"is_preprint":false,"journal":"Cancer Cell","published_at":1669852800.0,"published_day":1,"published_month":12,"published_year":2022},"revised_at":"2026-06-11T16:53:35+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"de2cde16-c8d3-4a6d-80be-1be9e879aaca","collection_url":"https://cellxgene.cziscience.com/collections/de2cde16-c8d3-4a6d-80be-1be9e879aaca","collection_version_id":"c71b0c73-ac5d-4a7b-a750-1a9e18355ab7","consortia":[],"contact_email":"emilprmu@gmail.com","contact_name":"Emil Kriukov","created_at":"2026-06-10T21:24:12+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"30c2a6fd-d547-460f-a5e7-44c62a2af7ad","dataset_version_id":"0be8ebd5-bb46-4bc7-a998-f24ce59bb28a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"open-angle glaucoma","ontology_term_id":"MONDO:0005338"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Our previous study suggests that CD4+ T cells primed by bacterial heat shock proteins (HSP) mediate an autoimmune mechanism contributing to the pathogenesis of glaucoma. The present study showed that the activity of CD4+ T cells from the peripheral blood mononuclear cells (PBMC) of POAG patients was significantly higher than control subjects as revealed by single-cell RNA sequencing. The notion of antigenic mimicry between gut bacteria and mouse HSPs expressed in the eye causes glaucomatous degeneration remains unclear. Here, we report that the induction of immune tolerance by nasal administration of bacterial HSP60 protein led to an increase in regulatory T (Tr1) cells and suppression of HSP-specific Th1 cell frequencies in glaucoma mice. leading to protections against retinal ganglion cell loss and preservation of spatial vision in glaucoma mice. Moreover, this neuroprotective effect on retinal ganglion cells in HSP-immune-tolerant mice was compromised by IL-10 deficiency. Our data suggests that induction of immune tolerance to HSP60 presents a potential therapeutic strategy protecting against retinal degeneration and vision loss in glaucoma by partial restoration of T cell-mediated immune balance.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/mcrewcow/PBMC_Glaucoma_human"},{"link_name":"GSE268936","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE268936"}],"name":"Human PBMC Glaucoma Atlas - Immune Tolerance to HSP60 Attenuates Neurodegeneration in Glaucoma","published_at":"2025-08-13T21:58:45+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:55:44+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"59c9ecfe-c47d-4a6a-bab0-895cc0c1942b","collection_url":"https://cellxgene.cziscience.com/collections/59c9ecfe-c47d-4a6a-bab0-895cc0c1942b","collection_version_id":"04e39551-d05e-4768-a1fe-d8c8c7c9ae0c","consortia":[],"contact_email":"twc@stanford.edu","contact_name":"Tony Wyss-Coray","created_at":"2026-06-10T02:43:00+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"595c9010-99ec-462d-b6a1-2b2fe5407871","dataset_version_id":"6dd04cc1-f4b6-49c4-b34c-56508ea8af8c","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"aspiration pneumonia","ontology_term_id":"MONDO:0000265"},{"label":"influenza","ontology_term_id":"MONDO:0005812"},{"label":"malignant pancreatic neoplasm","ontology_term_id":"MONDO:0009831"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"choroid plexus","ontology_term_id":"UBERON:0001886","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"2f05ab20-a092-4bab-9276-3e0eb24e3fee","dataset_version_id":"c4ee3adc-893f-449a-988c-b3b4d51ceba9","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"breast cancer","ontology_term_id":"MONDO:0007254"},{"label":"cardiomyopathy","ontology_term_id":"MONDO:0004994"},{"label":"chronic obstructive pulmonary disease","ontology_term_id":"MONDO:0005002"},{"label":"heart disorder","ontology_term_id":"MONDO:0005267"},{"label":"influenza","ontology_term_id":"MONDO:0005812"},{"label":"myocardial infarction","ontology_term_id":"MONDO:0005068"},{"label":"small cell lung carcinoma","ontology_term_id":"MONDO:0008433"},{"label":"tongue cancer","ontology_term_id":"MONDO:0004631"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"medial orbital frontal cortex","ontology_term_id":"UBERON:0022352","tissue_type":"tissue"}]}],"description":"Although SARS-CoV-2 primarily targets the respiratory system, patients with and survivors of COVID-19 can suffer neurological symptoms1,2,3. However, an unbiased understanding of the cellular and molecular processes that are affected in the brains of patients with COVID-19 is missing. Here we profile 65,309 single-nucleus transcriptomes from 30 frontal cortex and choroid plexus samples across 14 control individuals (including 1 patient with terminal influenza) and 8 patients with COVID-19. Although our systematic analysis yields no molecular traces of SARS-CoV-2 in the brain, we observe broad cellular perturbations indicating that barrier cells of the choroid plexus sense and relay peripheral inflammation into the brain and show that peripheral T cells infiltrate the parenchyma. We discover microglia and astrocyte subpopulations associated with COVID-19 that share features with pathological cell states that have previously been reported in human neurodegenerative disease4,5,6. Synaptic signalling of upper-layer excitatory neurons\u2014which are evolutionarily expanded in humans7 and linked to cognitive function8\u2014is preferentially affected in COVID-19. Across cell types, perturbations associated with COVID-19 overlap with those found in chronic brain disorders and reside in genetic variants associated with cognition, schizophrenia and depression. Our findings and public dataset provide a molecular framework to understand current observations of COVID-19-related neurological disease, and any such disease that may emerge at a later date.","doi":"10.1038/s41586-021-03710-0","is_pre_analysis":false,"links":[{"link_name":"GSE159812","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159812"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://twc-stanford.shinyapps.io/scRNA_Brain_COVID19"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.ccb.uni-saarland.de/"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://web.stanford.edu/group/twclab/cgi-bin/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/72ff4818-5692-4bbc-8886-e47763531023"}],"name":"Dysregulation of brain and choroid plexus cell types in severe COVID-19","published_at":"2024-02-07T17:08:41+00:00","publisher_metadata":{"authors":[{"family":"Yang","given":"Andrew C."},{"family":"Kern","given":"Fabian"},{"family":"Losada","given":"Patricia M."},{"family":"Agam","given":"Maayan R."},{"family":"Maat","given":"Christina A."},{"family":"Schmartz","given":"Georges P."},{"family":"Fehlmann","given":"Tobias"},{"family":"Stein","given":"Julian A."},{"family":"Schaum","given":"Nicholas"},{"family":"Lee","given":"Davis P."},{"family":"Calcuttawala","given":"Kruti"},{"family":"Vest","given":"Ryan T."},{"family":"Berdnik","given":"Daniela"},{"family":"Lu","given":"Nannan"},{"family":"Hahn","given":"Oliver"},{"family":"Gate","given":"David"},{"family":"McNerney","given":"M. Windy"},{"family":"Channappa","given":"Divya"},{"family":"Cobos","given":"Inma"},{"family":"Ludwig","given":"Nicole"},{"family":"Schulz-Schaeffer","given":"Walter J."},{"family":"Keller","given":"Andreas"},{"family":"Wyss-Coray","given":"Tony"}],"is_preprint":false,"journal":"Nature","published_at":1626912000.0,"published_day":22,"published_month":7,"published_year":2021},"revised_at":"2026-06-11T16:53:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c26ca66a-63ea-4059-a24e-0e0be0a2a173","collection_url":"https://cellxgene.cziscience.com/collections/c26ca66a-63ea-4059-a24e-0e0be0a2a173","collection_version_id":"63c03d17-6526-4e0a-8e6c-0988f3cb053a","consortia":[],"contact_email":"semil.choksi@ucsf.edu","contact_name":"Semil Choksi","created_at":"2026-06-10T06:45:49+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ae9e6a8c-83d6-4870-a7aa-e604f1c01752","dataset_version_id":"b588800f-1e97-4439-ad99-9ec986c1af61","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"tracheal epithelial cell","ontology_term_id":"CL:0000307","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"93dd56b0-5cac-4a99-b5cc-e0f2af2fd6b4","dataset_version_id":"88a39203-1c3d-4388-90d3-18f335695b9c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"tracheal epithelial cell","ontology_term_id":"CL:0000307","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"732a691e-4504-4226-aecf-5d627e062efc","dataset_version_id":"9ba89a98-495d-4d52-a1c7-ea3582e81644","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"tracheal epithelial cell","ontology_term_id":"CL:0000307","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"659f6e10-86fd-4b76-bc5e-34f9a09f1580","dataset_version_id":"43fab65c-c1b8-468b-8137-484b6eb7b4bd","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus 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cell","ontology_term_id":"CL:0000307","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"10a44ac3-09a6-42d1-9052-179e20bb2261","dataset_version_id":"b078f9bb-a778-4686-9562-364f9773eb74","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"tracheal epithelial cell","ontology_term_id":"CL:0000307","tissue_type":"primary cell culture"}]}],"description":"The canonical mitotic cell cycle coordinates DNA replication, centriole duplication and cytokinesis to generate two cells from one. Some cells, such as mammalian trophoblast giant cells, employ cell cycle variants like the endocycle to bypass mitosis. Differentiating multiciliated cells, found in the mammalian airway, brain ventricles and reproductive tracts, are post-mitotic but generate hundreds of centrioles, each of which matures into a basal body and nucleates a motile cilium. Several cell cycle regulators have previously been implicated in specific steps of multiciliated cell differentiation. We found that differentiating multiciliated cells integrate cell cycle regulators into a novel cell cycle variant, which we refer to as the multiciliation cycle. The multiciliation cycle redeploys many canonical cell cycle regulators, including cyclin-dependent kinases (CDKs) and their cognate cyclins. For example, Cyclin D1-CDK4/6, regulators of mitotic G1 to S progression, are required to initiate multiciliated cell differentiation. The multiciliation cycle amplifies some aspects of the canonical cell cycle, such as centriole synthesis, and blocks others, such as DNA replication. E2F7, a transcriptional regulator of canonical S to G2 progression, is expressed at high levels during the multiciliation cycle. In the multiciliation cycle, E2F7 directly dampens expression of genes encoding DNA replication machinery and terminates the S phase-like gene expression program. Loss of E2F7 causes a reacquisition of DNA synthesis in multiciliated cells and dysregulation of multiciliation cycle progression, disrupting centriole maturation and ciliogenesis. We conclude that multiciliated cells employ an alternative cell cycle that, instead of controlling proliferation, orchestrates differentiation.","doi":"10.1038/s41586-024-07476-z","is_pre_analysis":false,"links":[{"link_name":"GSE228110","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE228110"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/lb15/multiciliation_cycle"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/10896100"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/10896066"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/10896071"}],"name":"An alternative cell cycle coordinates multiciliated cell differentiation","published_at":"2024-03-27T21:24:22+00:00","publisher_metadata":{"authors":[{"family":"Choksi","given":"Semil P."},{"family":"Byrnes","given":"Lauren E."},{"family":"Konjikusic","given":"Mia J."},{"family":"Tsai","given":"Benedict W. H."},{"family":"Deleon","given":"Rachel"},{"family":"Lu","given":"Quanlong"},{"family":"Westlake","given":"Christopher J."},{"family":"Reiter","given":"Jeremy F."}],"is_preprint":false,"journal":"Nature","published_at":1716940800.0,"published_day":29,"published_month":5,"published_year":2024},"revised_at":"2026-06-11T16:53:44+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3b8b7fec-ed65-4483-9579-9f98f5a93a74","collection_url":"https://cellxgene.cziscience.com/collections/3b8b7fec-ed65-4483-9579-9f98f5a93a74","collection_version_id":"e12c085a-23cc-4fcc-9217-ffcf3806d4ce","consortia":[],"contact_email":"karakashet@chop.edu","contact_name":"Tatiana Karakasheva","created_at":"2026-06-10T02:51:52+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"944dedde-03e5-456d-996d-7250f7247b85","dataset_version_id":"517c552c-48ff-4f15-9f23-55a70f3f054b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"right colon","ontology_term_id":"UBERON:0008972","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5d4415d1-cfcd-4b43-b2b2-138b5afd68af","dataset_version_id":"45566c3d-0484-4b2b-858b-8aea1783f21f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"right colon","ontology_term_id":"UBERON:0008972","tissue_type":"tissue"}]}],"description":"This dataset comprises endoscopic biopsies from 23 control subjects: 12 pediatric patients with no pathological diagnosis in the lower GI tract and 11 healthy adults. To enrich for transcriptomes from live epithelial cells, each biopsy was separated into epithelial and stromal fractions via crypt scraping (our protocol is described in detail here), and single cell RNA-seq libraries were generated using 10x Chromium technology. The resulting dataset contains 12 clusters (epithelium, CD4+ T cell, CD8+ T cell, B cell, plasma cell, macrophage, mast cell, endothelium, fibroblast, myofibroblast, pericyte, glia), and the epithelium is further divided into 12 sub-clusters (stem cells, transit amplifying (TA) cells, early progenitors, OLFM4+REG1A+ secretory progenitors, OLFM4-REG1A+ secretory progenitors, absorptive colonocyte progenitors, FABP1+ absorptive colonocytes, AQP8+ absorptive colonocytes, BEST4+ colonocytes , goblet cells, tuft cells, and M cells). This dataset presents a resource for interrogating the biology of specialized cell types in the colonic mucosa at homeostasis along the pediatric-to-adult continuum.","doi":"10.1016/j.jcmgh.2025.101665","is_pre_analysis":false,"links":[{"link_name":"GSE305528","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305528"}],"name":"Epithelium-enriched single cell transcriptomes from the ascending colon of pediatric and adult control subjects","published_at":"2026-02-12T19:48:49+00:00","publisher_metadata":{"authors":[{"family":"Karakasheva","given":"Tatiana A."},{"family":"Martinez","given":"Clara Morral"},{"family":"Zhou","given":"Yusen"},{"family":"Qui","given":"Jingya"},{"family":"Chen","given":"Xinyi E."},{"family":"Soto","given":"Gloria E."},{"family":"Nettleford","given":"Shaneice K."},{"family":"Hix","given":"Olivia T."},{"family":"Roach","given":"Daana M."},{"family":"Laguerta","given":"Alyssa M."},{"family":"Thadi","given":"Anusha"},{"family":"Edwards","given":"Rachael M."},{"family":"Aleynick","given":"Daniel"},{"family":"Weinbrom","given":"Sarah"},{"family":"Borodyanskaya","given":"Elizaveta"},{"family":"Pickering","given":"Oliver H."},{"family":"Fulton","given":"MaryKate"},{"family":"Chen","given":"Chia-Hui"},{"family":"Peterson","given":"Isabella V."},{"family":"Hagen","given":"Erik B."},{"family":"Yannuzzi","given":"Ian P."},{"family":"Haider","given":"Zainab"},{"family":"Cramer","given":"Zvi"},{"family":"Conrad","given":"Maire A."},{"family":"Li","given":"Ning"},{"family":"Bewtra","given":"Meenakshi"},{"family":"Uzun","given":"Yasin"},{"family":"Tan","given":"Kai"},{"family":"Kelsen","given":"Judith R."},{"family":"Minn","given":"Andy J."},{"family":"Lengner","given":"Christopher J."},{"family":"Hamilton","given":"Kathryn E."}],"is_preprint":false,"journal":"Cellular and Molecular Gastroenterology and Hepatology","published_at":1767225600.0,"published_day":1,"published_month":1,"published_year":2026},"revised_at":"2026-06-11T16:53:45+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"939769a8-d8d2-4d01-abfc-55699893fd49","collection_url":"https://cellxgene.cziscience.com/collections/939769a8-d8d2-4d01-abfc-55699893fd49","collection_version_id":"893659bf-a2b9-4a3a-8d8d-57b9a4a054fe","consortia":[],"contact_email":"jasonah@gene.com","contact_name":"Jason A. 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To better understand disease pathogenesis and identify causal genes in GWAS loci for AMD risk, we present a comprehensive database of human retina and retinal pigment epithelium (RPE). Our database comprises macular and non-macular RNA sequencing (RNA-seq) profiles from 129 donors, a genome-wide expression quantitative trait loci (eQTL) dataset that includes macula-specific retina and RPE/choroid, and single-nucleus RNA-seq (NucSeq) from human retina and RPE with subtype resolution from more than 100,000 cells. Using NucSeq, we find enriched expression of AMD candidate genes in RPE cells. We identify 15 putative causal genes for AMD on the basis of co-localization of genetic association signals for AMD risk and eye eQTL, including the genes TSPAN10 and TRPM1. These results demonstrate the value of our human eye database for elucidating genetic pathways and potential therapeutic targets for ocular diseases.","doi":"10.1016/j.celrep.2019.12.082","is_pre_analysis":false,"links":[{"link_name":"GSE135133","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE135133"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP484/nucseq-from-human-control-eyes-scrnaseq"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/e090445c-6971-4212-bc5f-ae4ec3914102"}],"name":"Integration of eQTL and a Single-Cell Atlas in the Human Eye Identifies Causal Genes for Age-Related Macular Degeneration","published_at":"2023-03-31T22:01:25+00:00","publisher_metadata":{"authors":[{"family":"Orozco","given":"Luz D."},{"family":"Chen","given":"Hsu-Hsin"},{"family":"Cox","given":"Christian"},{"family":"Katschke","given":"Kenneth 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We hypothesize that this selective vulnerability is underpinned by physiological variation in white matter glia. Using single nucleus RNA sequencing of human post-mortem white matter samples from the brain, cerebellum and spinal cord and subsequent tissue-based validation we found substantial glial heterogeneity with tissue region: we identified region-specific oligodendrocyte precursor cells (OPCs) that retain developmental origin markers into adulthood, distinguishing them from mouse OPCs. Region-specific OPCs give rise to similar oligodendrocyte populations, however spinal cord oligodendrocytes exhibit markers such as SKAP2 which are associated with increased myelin production and we found a spinal cord selective population particularly equipped for producing long and thick myelin sheaths based on the expression of genes/proteins such as HCN2. Spinal cord microglia exhibit a more activated phenotype compared to brain microglia, suggesting that the spinal cord is a more pro-inflammatory environment, a difference that intensifies with age. Astrocyte gene expression correlates strongly with CNS region, however, astrocytes do not show a more activated state with region or age. Across all glia, sex differences are subtle but the consistent increased expression of protein-folding genes in male donors hints at pathways that may contribute to sex differences in disease susceptibility. These findings are essential to consider for understanding selective CNS pathologies and developing tailored therapeutic strategies.","doi":"10.1186/s40478-023-01568-z","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://seeker-science.shinyapps.io/shiny_app_multi/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Anna-Williams/Luise_Seeker_Human_WM_Glia"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/73011a86-4755-48ac-9f70-a28903b4ad77"}],"name":"Brain matters: Unveiling the Distinct Contributions of Region, Age, and Sex to Glia diversity and CNS Function","published_at":"2023-06-14T17:42:10+00:00","publisher_metadata":{"authors":[{"family":"Seeker","given":"Luise A."},{"family":"Bestard-Cuche","given":"Nadine"},{"family":"J\u00e4kel","given":"Sarah"},{"family":"Kazakou","given":"Nina-Lydia"},{"family":"B\u00f8strand","given":"Sunniva M. 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Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care. Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines that may be produced by a subset of inflammatory monocytes, lymphopenia, and T cell exhaustion. To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19.","doi":"10.1038/s41591-020-0944-y","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ajwilk/2020_Wilk_COVID"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://med.stanford.edu/blishlab.html"},{"link_name":"GEO","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150728"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-150728"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-periph-immuno"}],"name":"Single-cell atlas of peripheral immune response to SARS-CoV-2 infection","published_at":"2020-09-28T17:48:23+00:00","publisher_metadata":{"authors":[{"family":"Wilk","given":"Aaron J."},{"family":"Rustagi","given":"Arjun"},{"family":"Zhao","given":"Nancy Q."},{"family":"Roque","given":"Jonasel"},{"family":"Mart\u00ednez-Col\u00f3n","given":"Giovanny J."},{"family":"McKechnie","given":"Julia L."},{"family":"Ivison","given":"Geoffrey T."},{"family":"Ranganath","given":"Thanmayi"},{"family":"Vergara","given":"Rosemary"},{"family":"Hollis","given":"Taylor"},{"family":"Simpson","given":"Laura J."},{"family":"Grant","given":"Philip"},{"family":"Subramanian","given":"Aruna"},{"family":"Rogers","given":"Angela J."},{"family":"Blish","given":"Catherine A."}],"is_preprint":false,"journal":"Nat Med","published_at":1593561600.0,"published_day":1,"published_month":7,"published_year":2020},"revised_at":"2026-06-11T16:53:47+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0d35c0fd-ef0b-4b70-bce6-645a4660e5fa","collection_url":"https://cellxgene.cziscience.com/collections/0d35c0fd-ef0b-4b70-bce6-645a4660e5fa","collection_version_id":"49853d03-5d1d-4d6f-8c15-41e43204eabe","consortia":[],"contact_email":"icobos@stanford.edu","contact_name":"Inma Cobos","created_at":"2026-06-10T19:00:31+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"cff99df2-4904-44f7-9173-ff837f95606e","dataset_version_id":"7bfa165b-b3af-4f84-9a89-ca22d3e093f3","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"Brodmann (1909) area 17","ontology_term_id":"UBERON:8440010","tissue_type":"tissue"},{"label":"Brodmann (1909) area 7","ontology_term_id":"UBERON:0013538","tissue_type":"tissue"},{"label":"Brodmann (1909) area 9","ontology_term_id":"UBERON:0013540","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"215ede73-4f67-4a72-b77e-9c3b077b6dfc","dataset_version_id":"38669699-40a6-49c5-96f9-51c6f0700e28","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"Brodmann (1909) area 17","ontology_term_id":"UBERON:8440010","tissue_type":"tissue"},{"label":"Brodmann (1909) area 7","ontology_term_id":"UBERON:0013538","tissue_type":"tissue"},{"label":"Brodmann (1909) area 9","ontology_term_id":"UBERON:0013540","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"0ecea697-0f69-4d40-88e1-7f854e17e2b3","dataset_version_id":"c0d09937-0c24-43a4-8900-64b146ac4692","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"Brodmann (1909) area 17","ontology_term_id":"UBERON:8440010","tissue_type":"tissue"},{"label":"Brodmann (1909) area 7","ontology_term_id":"UBERON:0013538","tissue_type":"tissue"},{"label":"Brodmann (1909) area 9","ontology_term_id":"UBERON:0013540","tissue_type":"tissue"}]}],"description":"Single-cell omics is advancing our understanding of selective neuronal vulnerability in Alzheimer\u2019s disease (AD), revealing specific subtypes that are either susceptible or resilient to neurodegeneration. Using single-nucleus and spatial transcriptomics to examine neocortical regions affected early (prefrontal cortex and precuneus) or late (primary visual cortex) in AD, we identified a resilient excitatory population in layer 4 of the primary visual cortex expressing RORB, CUX2, and EYA4. Layer 4 neurons in association neocortex also remained relatively preserved as AD progressed and shared overlapping molecular signatures of resilience. Early in the disease, resilient neurons upregulated genes associated with synapse maintenance, synaptic plasticity, calcium homeostasis, and neuroprotection, including GRIN2A, RORA, NRXN1, NLGN1, NCAM2, FGF14, NRG3, NEGR1, and CSMD1. We also identified KCNIP4, which encodes a voltage-gated potassium (Kv) channel-interacting protein that interacts with Kv4.2 channels and presenilins, as a key factor linked to resilience. KCNIP4 was consistently upregulated in the early stages of pathology. Furthermore, AAV-mediated overexpression of Kcnip4 in a humanized AD mouse model reduced the expression of the activity-dependent genes Arc and c-Fos, suggesting compensatory mechanisms against neuronal hyperexcitability. Our dataset provides a valuable resource for investigating mechanisms underlying resilience to neurodegeneration.\n\nMETHODOLOGICAL NOTES: This single-nucleus RNA-seq dataset was generated from postmortem fresh-frozen human cerebral cortex from patients who died with AD and age-matched healthy controls. It contains 427,081 nuclei (after QC), of which approximately 85% are neurons, from the prefrontal (BA9), precuneus (BA7), and primary visual (BA17) cortices of 46 donors. These include 18 donors with no or low AD pathology (Braak 0\u2013II), 10 with intermediate AD pathology (Braak III\u2013IV), and 18 with high AD pathology (Braak V\u2013VI). The samples were processed according to our protocol at protocols.io. Each sample was sorted by FANS (fluorescence-activated nucleus sorting) to collect two populations: one consisting of all nuclei and the other enriched for neurons (NeuN+).","doi":"10.1038/s41467-026-68920-4","is_pre_analysis":false,"links":[{"link_name":"Sample processing protocol","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/isolation-of-single-nuclei-from-postmortem-fresh-f-6tuhenw"}],"name":"Molecular Signatures of Resilience to Alzheimer\u2019s Disease in Neocortical Layer 4 Neurons","published_at":"2024-11-07T17:02:13+00:00","publisher_metadata":{"authors":[{"family":"Dharshini","given":"S. Akila Parvathy"},{"family":"Sanz-Ros","given":"Jorge"},{"family":"Pan","given":"Jie"},{"family":"Tang","given":"Weijing"},{"family":"Vallejo","given":"Kristen"},{"family":"Liu","given":"Yu Chen"},{"family":"Otero-Garcia","given":"Marcos"},{"family":"Cobos","given":"Inma"}],"is_preprint":false,"journal":"Nat Commun","published_at":1769817600.0,"published_day":31,"published_month":1,"published_year":2026},"revised_at":"2026-06-11T16:53:48+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9c8808ce-1138-4dbe-818c-171cff10e650","collection_url":"https://cellxgene.cziscience.com/collections/9c8808ce-1138-4dbe-818c-171cff10e650","collection_version_id":"522b6add-7f14-49ab-87b3-295d1a1ddf38","consortia":[],"contact_email":"ebutcher@stanford.edu","contact_name":"Eugene Butcher","created_at":"2026-06-10T15:23:58+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"cfa3c355-ee77-4fc8-9a00-78e61d23024c","dataset_version_id":"c7684e46-78f3-486e-8912-744180e8a269","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cervical lymph node","ontology_term_id":"UBERON:0002429","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"26ae14da-9e5f-4d18-abae-18a5a328feef","dataset_version_id":"9f37b561-813c-425b-b614-25a9cad2bfe7","disease":[{"label":"lymphadenitis","ontology_term_id":"MONDO:0002052"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"peripheral lymph node","ontology_term_id":"UBERON:0003968","tissue_type":"tissue"}]}],"description":"Single-cell transcriptomics promises to revolutionize our understanding of the vasculature. Emerging computational methods applied to high dimensional single cell data allow integration of results between samples and species, and illuminate the diversity and underlying developmental and architectural organization of cell populations. Here, we illustrate these methods in analysis of mouse lymph node (LN) lymphatic endothelial cells (LEC) at single cell resolution. Clustering identifies five well-delineated subsets, including two medullary sinus subsets not recognized previously as distinct. Nearest neighbor alignments in trajectory space position the major subsets in a sequence that recapitulates known and suggests novel features of LN lymphatic organization, providing a transcriptional map of the lymphatic endothelial niches and of the transitions between them. Differences in gene expression reveal specialized programs for (1) subcapsular ceiling endothelial interactions with the capsule connective tissue and cells, (2) subcapsular floor regulation of lymph borne cell entry into the LN parenchyma and antigen presentation, and (3) medullary subset specialization for pathogen interactions and LN remodeling. LEC of the subcapsular sinus floor and medulla, which represent major sites of cell entry and exit from the LN parenchyma respectively, respond robustly to oxazolone inflammation challenge with enriched signaling pathways that converge on both innate and adaptive immune responses. Integration of mouse and human single-cell profiles reveals a conserved cross-species pattern of lymphatic vascular niches and gene expression, as well as specialized human subsets and genes unique to each species. The examples provided demonstrate the power of single-cell analysis in elucidating endothelial cell heterogeneity, vascular organization and endothelial cell responses. We discuss the findings from the perspective of LEC functions in relation to niche formations in the unique stromal and highly immunological environment of the LN.","doi":"10.3389/fcvm.2020.00052","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE143877"},{"link_name":"","link_type":"OTHER","link_url":"http://med.stanford.edu/butcherlab/data/scLEC.html"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145121"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.igp.uu.se/research/clinical_immunology/maria-ulvmar/"}],"name":"A single-cell transcriptional roadmap of the mouse and human lymph node lymphatic vasculature","published_at":"2021-03-22T18:32:16+00:00","publisher_metadata":{"authors":[{"family":"Xiang","given":"Menglan"},{"family":"Grosso","given":"Rub\u00e9n Adri\u00e1n"},{"family":"Takeda","given":"Akira"},{"family":"Pan","given":"Junliang"},{"family":"Bekkhus","given":"Tove"},{"family":"Brulois","given":"Kevin"},{"family":"Dermadi","given":"Denis"},{"family":"Nordling","given":"Sofia"},{"family":"Vanlandewijck","given":"Michael"},{"family":"Jalkanen","given":"Sirpa"},{"family":"Ulvmar","given":"Maria H."},{"family":"Butcher","given":"Eugene C."}],"is_preprint":false,"journal":"Front. 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disease","ontology_term_id":"MONDO:0005016"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"}]}],"description":"High resolution spatial transcriptomics is a transformative technology that enables mapping of RNA expression directly from intact tissue sections; however, its utility for the elucidation of disease processes and therapeutically actionable pathways remain largely unexplored. Here we applied Slide-seqV2 to mouse and human kidneys, in healthy and in distinct disease paradigms. First, we established the feasibility of Slide-seqV2 in human kidney by analyzing tissue from 9 distinct donors, which revealed a cell neighborhood centered around a population of LYVE1+ macrophages. Second, in a mouse model of diabetic kidney disease, we detected changes in the cellular organization of the spatially-restricted kidney filter and blood flow regulating apparatus. Third, in a mouse model of a toxic proteinopathy, we identified previously unknown, disease-specific cell neighborhoods centered around macrophages. In a spatially-restricted subpopulation of epithelial cells, we also found perturbations in 77 genes associated with the unfolded protein response (UPR), including Tmed9. Treatment with a TMED9-targeting compound showed efficient removal of toxic mutant proteins and reversal of the UPR. Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods and actionable targets.","doi":"10.1016/j.isci.2022.104097","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE190094"},{"link_name":"Kidney Slide-seq Github","link_type":"OTHER","link_url":"https://github.com/marshalljamie/Kidney-Slide-seq"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/library-generation-using-slide-seqv2-bpgzmjx6"},{"link_name":"Macosko Lab Slide-seq Github","link_type":"OTHER","link_url":"https://github.com/MacoskoLab/slideseq-tools"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://grekalab.org/"}],"name":"High Resolution Slide-seqV2 Spatial Transcriptomics Enables Discovery of Disease-Specific Cell Neighborhoods and Pathways","published_at":"2021-12-09T18:27:10+00:00","publisher_metadata":{"authors":[{"family":"Marshall","given":"Jamie L."},{"family":"Noel","given":"Teia"},{"family":"Wang","given":"Qingbo S."},{"family":"Chen","given":"Haiqi"},{"family":"Murray","given":"Evan"},{"family":"Subramanian","given":"Ayshwarya"},{"family":"Vernon","given":"Katherine A."},{"family":"Bazua-Valenti","given":"Silvana"},{"family":"Liguori","given":"Katie"},{"family":"Keller","given":"Keith"},{"family":"Stickels","given":"Robert R."},{"family":"McBean","given":"Breanna"},{"family":"Heneghan","given":"Rowan M."},{"family":"Weins","given":"Astrid"},{"family":"Macosko","given":"Evan Z."},{"family":"Chen","given":"Fei"},{"family":"Greka","given":"Anna"}],"is_preprint":false,"journal":"iScience","published_at":1648771200.0,"published_day":1,"published_month":4,"published_year":2022},"revised_at":"2026-06-11T16:53:57+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"cae8bad0-39e9-4771-85a7-822b0e06de9f","collection_url":"https://cellxgene.cziscience.com/collections/cae8bad0-39e9-4771-85a7-822b0e06de9f","collection_version_id":"7c1b34a3-6ddf-4cd9-8d4d-7a16ce98676a","consortia":[],"contact_email":"marcos.assisnascimento@ucsf.edu","contact_name":"Marcos Assis Nascimento","created_at":"2026-06-10T01:11:52+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ecce9688-66ea-4600-98f7-84aed7421c01","dataset_version_id":"690cd774-112b-489d-af6c-8fd8aa2de80b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"entorhinal cortex","ontology_term_id":"UBERON:0002728","tissue_type":"tissue"},{"label":"ganglionic eminence","ontology_term_id":"UBERON:0004023","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"72822932-10f6-466f-baf3-a2c1d89364bc","dataset_version_id":"08996e18-e97e-4da6-bb27-af5eb4456e85","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"entorhinal cortex","ontology_term_id":"UBERON:0002728","tissue_type":"tissue"},{"label":"ganglionic eminence","ontology_term_id":"UBERON:0004023","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"24584be9-d3d5-49c3-a042-99c18fe324db","dataset_version_id":"55a75aef-bc7a-4ed0-b9de-80e3139caa49","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"entorhinal cortex","ontology_term_id":"UBERON:0002728","tissue_type":"tissue"}]}],"description":"The human brain's temporal lobe contains the entorhinal cortex (EC), a highly interconnected integrative hub for sensory and spatial information; key for episodic memory formation and the primary source of cortical hippocampal inputs.  The human EC continues to develop during childhood, yet neurogenesis and neuronal migration to the EC are widely considered complete by birth.  Here we show that the human temporal lobe contains many young neurons migrating into the postnatal EC and adjacent regions; with a large tangential stream persisting ~1 year and radial dispersal until ~2-3 years.  In contrast, we found no equivalent postnatal migration in rhesus macaque (Macaca mulatta).  Immunostaining and single-nuclei RNA-seq (snRNA-seq) of ganglionic eminence (GE) germinal zones, EC stream, and postnatal EC reveals that most EC stream migrating cells are derived from the caudal GE and become LAMP5+RELN+ inhibitory interneurons. These late-arriving interneurons could continue to shape the processing of sensory and spatial information well into postnatal life when children are actively interacting with their environment. The EC is one of the first brain regions affected in Alzheimer\u2019s disease and recent work links the decline in cognitive function to the loss of LAMP5+RELN+ cells. Our investigation reveals that many of these cells arrive in the EC through a major postnatal migratory stream in early childhood.","doi":"10.1038/s41586-023-06981-x","is_pre_analysis":false,"links":[{"link_name":"GSE199762","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE199762"},{"link_name":"phs003509","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003509"}],"name":"Protracted Neuronal Recruitment in the Temporal Lobe of Young Children","published_at":"2024-01-11T16:54:23+00:00","publisher_metadata":{"authors":[{"family":"Nascimento","given":"Marcos Assis"},{"family":"Biagiotti","given":"Sean"},{"family":"Herranz-P\u00e9rez","given":"Vicente"},{"family":"Santiago","given":"Samara"},{"family":"Bueno","given":"Raymund"},{"family":"Ye","given":"Chun J."},{"family":"Abel","given":"Taylor J."},{"family":"Zhang","given":"Zhuangzhi"},{"family":"Rubio-Moll","given":"Juan S."},{"family":"Kriegstein","given":"Arnold R."},{"family":"Yang","given":"Zhengang"},{"family":"Garcia-Verdugo","given":"Jose Manuel"},{"family":"Huang","given":"Eric J."},{"family":"Alvarez-Buylla","given":"Arturo"},{"family":"Sorrells","given":"Shawn F."}],"is_preprint":false,"journal":"Nature","published_at":1709164800.0,"published_day":29,"published_month":2,"published_year":2024},"revised_at":"2026-06-11T16:54:01+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"f70ebd97-b3bc-44fe-849d-c18e08fe773d","collection_url":"https://cellxgene.cziscience.com/collections/f70ebd97-b3bc-44fe-849d-c18e08fe773d","collection_version_id":"c052b020-9c1a-470b-ba8c-b207c7994ae4","consortia":[],"contact_email":"emacosko@broadinstitute.org","contact_name":"Evan Macosko","created_at":"2026-06-10T08:37:18+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"e0ed3c55-aff6-4bb7-b6ff-98a2d90b890c","dataset_version_id":"64c8b6a7-ac09-4ceb-8ad3-eaf512ea2ac2","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"}]}],"description":"The cerebellum is a well-studied brain structure with diverse roles in motor learning, coordination, cognition, and autonomic regulation. Nonetheless, a complete inventory of cerebellar cell types is presently lacking. We used high-throughput transcriptional profiling to molecularly define cell types across individual lobules of the adult mouse cerebellum. Purkinje and granule neurons showed considerable regional specialization, with the greatest diversity occurring in the posterior lobules. For multiple types of cerebellar interneurons, the molecular variation within each type was more continuous, rather than discrete. For the unipolar brush cells (UBCs)\u2014an interneuron population previously subdivided into two discrete populations\u2014the continuous variation in gene expression was associated with a graded continuum of electrophysiological properties. Most surprisingly, we found that molecular layer interneurons (MLIs) were composed of two molecularly and functionally distinct types. Both show a continuum of morphological variation through the thickness of the molecular layer, but electrophysiological recordings revealed marked differences between the two types in spontaneous firing, excitability, and electrical coupling. Together, these findings provide the first comprehensive cellular atlas of the cerebellar cortex, and outline a methodological and conceptual framework for the integration of molecular, morphological, and physiological ontologies for defining brain cell types.","doi":"10.1101/2020.03.04.976407","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/fresh-frozen-mouse-brain-preparation-for-single-nu-j8nlkedb1l5r/v1"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/hcr-of-patched-recorded-cerebellar-molecular-layer-14egn84n6g5d/v1"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://macoskolab.com/"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/frozen-tissue-nuclei-extraction-for-10xv3-snseq-rm7vz861xvx1/v1"}],"name":"A transcriptomic atlas of the mouse cerebellum reveals regional specializations and novel cell types","published_at":"2021-03-08T22:09:46+00:00","publisher_metadata":{"authors":[{"family":"Kozareva","given":"Velina"},{"family":"Martin","given":"Caroline"},{"family":"Osorno","given":"Tomas"},{"family":"Rudolph","given":"Stephanie"},{"family":"Guo","given":"Chong"},{"family":"Vanderburg","given":"Charles"},{"family":"Nadaf","given":"Naeem"},{"family":"Regev","given":"Aviv"},{"family":"Regehr","given":"Wade"},{"family":"Macosko","given":"Evan"}],"is_preprint":true,"journal":"bioRxiv","published_at":1583366400.0,"published_day":5,"published_month":3,"published_year":2020},"revised_at":"2026-06-11T16:54:03+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d5cad3f0-56b6-4fbe-8f2b-be92a8c7820f","collection_url":"https://cellxgene.cziscience.com/collections/d5cad3f0-56b6-4fbe-8f2b-be92a8c7820f","collection_version_id":"07a35908-e342-40d0-b03c-65d65ddc3c1a","consortia":[],"contact_email":"pcamara@pennmedicine.upenn.edu","contact_name":"Pablo G. 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The complex array of thalamic nuclei develops from a restricted pool of neural progenitors. We apply longitudinal single-cell RNA-sequencing and regional abrogation of Sonic hedgehog (Shh) to map the developmental trajectories of thalamic progenitors, intermediate progenitors, and post-mitotic neurons as they coalesce into distinct thalamic nuclei. These data reveal that the complex architecture of the thalamus is established early during embryonic brain development through the coordinated action of four cell differentiation lineages derived from Shh-dependent and independent progenitors. We systematically characterize the gene expression programs that define these thalamic lineages across time and demonstrate how their disruption upon Shh depletion causes pronounced locomotor impairment resembling infantile Parkinson\u2019s disease. 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Although much has been learned about their physiology and their Madagascar ecology and phylogeny, little is known about their cellular and molecular biology. Here we used droplet- and plate-based single cell RNA-sequencing to profile 226,000 cells from 27 mouse lemur organs and tissues opportunistically procured from four donors clinically and histologically characterized. Using computational cell clustering, integration, and expert cell annotation, we defined and biologically organized over 750 mouse lemur molecular cell types and their full gene expression profiles. These include cognates of most classical human cell types, including stem and progenitor cells, and the developmental programs for spermatogenesis, hematopoiesis, and other adult tissues. We also described dozens of previously unidentified or sparsely characterized cell types and subtypes. We globally compared cell type expression profiles to define the molecular relationships of cell types across the body, and explored primate cell and gene expression evolution by comparing mouse lemur cell transcriptomes to those of human, mouse, and macaque. This revealed cell type specific patterns of primate specialization, as well as many cell types and genes for which lemur provides a better human model than mouse. The atlas provides a cellular and molecular foundation for studying this primate model organism, and establishes a general approach for other emerging model organisms.","doi":"10.1038/s41586-025-09113-9","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://tabula-microcebus.sf.czbiohub.org/"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://cells.ucsc.edu/?ds=tabula-microcebus"},{"link_name":"Globus","link_type":"RAW_DATA","link_url":"https://app.globus.org/file-manager?origin_id=c9fc0a15-54a0-4182-8d64-fd8afc12f1fc&origin_path=%2F"}],"name":"Tabula Microcebus: A transcriptomic cell atlas of mouse lemur, an emerging primate model organism","published_at":"2025-11-11T21:05:02+00:00","publisher_metadata":{"authors":[{"name":"The Tabula Microcebus Consortium"},{"family":"de Morree","given":"Antoine"},{"family":"De Vlaminck","given":"Iwijn"},{"family":"Shapiro","given":"Liza"},{"family":"Razafindrakoto","given":"Andriamahery"},{"family":"Ravelonjanahary","given":"Hajanirina No\u00ebline"},{"family":"Wright","given":"Patricia"},{"family":"Yoder","given":"Anne D."},{"family":"Williams","given":"Cathy V."},{"family":"Schopler","given":"Robert"},{"family":"Radespiel","given":"Ute"},{"family":"Verdier","given":"Jean-Michel"},{"family":"Lautier","given":"Corinne"},{"family":"Kirk","given":"E. 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Brent Ferrell","created_at":"2026-06-10T11:01:51+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"19e46756-9100-4e01-8b0e-23b557558a4c","dataset_version_id":"cede8227-2c85-4f93-ab0a-73efc6b45f17","disease":[{"label":"clonal hematopoiesis","ontology_term_id":"MONDO:0100542"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Clonal hematopoiesis (CH) is an age-associated phenomenon that increases risk for hematologic malignancy and cardiovascular disease. CH is thought to enhance disease risk through inflammation in the peripheral blood. Here, we profile peripheral blood gene expression in 66,968 single cells from a cohort of 17 CH patients and 7 controls. Using a novel mitochondrial DNA barcoding approach, we were able to identify and separately compare mutant TET2 and DNMT3A cells to non-mutant counterparts. We discovered the vast majority of mutated cells were in the myeloid compartment. Additionally, patients harboring DNMT3A and TET2 CH mutations possessed a pro-inflammatory profile in CD14+ monocytes through previously unrecognized pathways such as galectin and macrophage Inhibitory Factor (MIF). We also found that T cells from CH patients, though mostly un-mutated, had decreased expression of GTPase of the immunity associated protein (GIMAP) genes, which are critical to T cell development, suggesting that CH may impair T cell function.","doi":"10.1182/bloodadvances.2023011445","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://osf.io/rac5w/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/bicklab/Single_Cell_CHIP_Multiomics"}],"name":"Multiomic Profiling of Human Clonal Hematopoiesis Reveals Genotype and Cell-Specific Inflammatory Pathway Activation","published_at":"2024-03-26T17:58:56+00:00","publisher_metadata":{"authors":[{"family":"Heimlich","given":"J. 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By single-nuclei RNA-sequencing (snRNA-seq) of over 20,000 differentiating white and brown preadipocytes, we constructed a high-resolution temporal transcriptional landscape of human white and brown adipogenesis. White and brown preadipocytes were isolated from a single individual's neck region, thereby eliminating inter-subject variability across two distinct lineages. These preadipocytes were also immortalized to allow for controlled, in vitro differentiation, allowing sampling of distinct cellular states across the spectrum of adipogenic progression. Pseudotemporal cellular ordering revealed the dynamics of ECM remodeling during early adipogenesis, and lipogenic/thermogenic response during late white/brown adipogenesis. Comparison with adipogenic regulation in murine models Identified several novel transcription factors as potential targets for adipogenic/thermogenic drivers in humans. Among these novel candidates, we explored the role of TRPS1 in adipocyte differentiation and showed that its knockdown impairs white adipogenesis in vitro. Key adipogenic and lipogenic markers revealed in our analysis were applied to analyze publicly available scRNA-seq datasets; these confirmed unique cell maturation features in recently discovered murine preadipocytes, and revealed inhibition of adipogenic expansion in humans with obesity. Overall, our study presents a comprehensive molecular description of both white and brown adipogenesis in humans and provides an important resource for future studies of adipose tissue development and function in both health and metabolic disease state.","doi":"10.1016/j.molmet.2023.101746","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://link.springer.com/protocol/10.1007/978-1-4939-6820-6_8"},{"link_name":"phs002461","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002461"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/streetslab/Adipogenesis_time_course"}],"name":"Mapping the transcriptional landscape of human white and brown adipogenesis using single-nuclei RNA-seq","published_at":"2023-06-16T20:25:45+00:00","publisher_metadata":{"authors":[{"family":"Gupta","given":"Anushka"},{"family":"Efthymiou","given":"Vissarion"},{"family":"Kodani","given":"Sean 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SEA-AD is supported by the National Institutes on Aging (NIA) grant U19AG060909. \n\nIMPORTANT: The \u201cDownload\u201d buttons below lead to a version of the dataset with dramatically reduced metadata and a reduced number of genes due to inconsistencies between the genome annotation in 10x Genomic\u2019s official human reference and the one used by CELLxGENE. For download purposes, we STRONGLY RECOMMEND using the full, official dataset by using the \u201cDOWNLOAD OFFICIAL DATASET\u201d link on the right that takes you to our AWS Open Data Registry.\n\nStudy data were generated from postmortem brain tissue obtained from the University of Washington BioRepository and Integrated Neuropathology (BRaIN) laboratory and Precision Neuropathology Core, which is supported by the NIH grants for the UW Alzheimer's Disease Research Center (P50AG005136 and P30AG066509) and the Adult Changes in Thought Study (U01AG006781 and U19AG066567). The ACT study is a longitudinal population-based prospective cohort study of brain aging and incident dementia in the Seattle metropolitan area. ACT is a repository at the Kaiser Permanente Washington Health Research Institute, which has established policies and procedures for sharing data with external investigators. Data available from this study web site do not require any additional Institutional Review Board (IRB) approval or permissions.","doi":"10.1038/s41593-024-01774-5","is_pre_analysis":false,"links":[{"link_name":"UW Alzheimer's Disease Research Center","link_type":"OTHER","link_url":"http://depts.washington.edu/mbwc/adrc"},{"link_name":"Adult Changes in Thought Study","link_type":"OTHER","link_url":"https://actagingresearch.org/"},{"link_name":"UW BioRepository and Integrated Neuropathology","link_type":"OTHER","link_url":"https://dlmp.uw.edu/research-labs/keene/BRaIN-lab"},{"link_name":"SEA-AD Homepage","link_type":"OTHER","link_url":"https://portal.brain-map.org/explore/seattle-alzheimers-disease"},{"link_name":"AD Knowledge Portal","link_type":"RAW_DATA","link_url":"https://adknowledgeportal.synapse.org/Explore/Studies/DetailsPage/StudyData?Study=syn26223298"},{"link_name":"DOWNLOAD OFFICIAL 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Despite extensive research, disease heterogeneity is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA sequencing to study the heterogeneity of 40 individuals along the multiple myeloma progression spectrum, including 11 healthy controls, demonstrating high interindividual variability that can be explained by expression of known multiple myeloma drivers and additional putative factors. We identify extensive subclonal structures for 10 of 29 individuals with multiple myeloma. In asymptomatic individuals with early disease and in those with minimal residual disease post-treatment, we detect rare tumor plasma cells with molecular characteristics similar to those of active myeloma, with possible implications for personalized therapies. Single cell analysis of rare circulating tumor cells allows for accurate liquid biopsy and detection of malignant plasma cells, which reflect bone marrow disease. Our work establishes single cell RNA sequencing for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients.","doi":"10.1038/s41591-018-0269-2","is_pre_analysis":false,"links":[{"link_name":"GSE117156","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117156"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/a29952d9-925e-40f4-8a1c-274f118f1f51"}],"name":"Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma","published_at":"2023-04-06T18:57:24+00:00","publisher_metadata":{"authors":[{"family":"Ledergor","given":"Guy"},{"family":"Weiner","given":"Assaf"},{"family":"Zada","given":"Mor"},{"family":"Wang","given":"Shuang-Yin"},{"family":"Cohen","given":"Yael C."},{"family":"Gatt","given":"Moshe E."},{"family":"Snir","given":"Nimrod"},{"family":"Magen","given":"Hila"},{"family":"Koren-Michowitz","given":"Maya"},{"family":"Herzog-Tzarfati","given":"Katrin"},{"family":"Keren-Shaul","given":"Hadas"},{"family":"Bornstein","given":"Chamutal"},{"family":"Rotkopf","given":"Ron"},{"family":"Yofe","given":"Ido"},{"family":"David","given":"Eyal"},{"family":"Yellapantula","given":"Venkata"},{"family":"Kay","given":"Sigalit"},{"family":"Salai","given":"Moshe"},{"family":"Ben Yehuda","given":"Dina"},{"family":"Nagler","given":"Arnon"},{"family":"Shvidel","given":"Lev"},{"family":"Orr-Urtreger","given":"Avi"},{"family":"Halpern","given":"Keren Bahar"},{"family":"Itzkovitz","given":"Shalev"},{"family":"Landgren","given":"Ola"},{"family":"San-Miguel","given":"Jesus"},{"family":"Paiva","given":"Bruno"},{"family":"Keats","given":"Jonathan J."},{"family":"Papaemmanuil","given":"Elli"},{"family":"Avivi","given":"Irit"},{"family":"Barbash","given":"Gabriel I."},{"family":"Tanay","given":"Amos"},{"family":"Amit","given":"Ido"}],"is_preprint":false,"journal":"Nat Med","published_at":1543622400.0,"published_day":1,"published_month":12,"published_year":2018},"revised_at":"2026-06-11T16:54:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9132fae8-bdfe-480f-9e45-45bc77f320b3","collection_url":"https://cellxgene.cziscience.com/collections/9132fae8-bdfe-480f-9e45-45bc77f320b3","collection_version_id":"6c0ed1d0-347d-408e-9b71-2167bc6b2573","consortia":[],"contact_email":"zhuang@chemistry.harvard.edu","contact_name":"Xiaowei Zhuang","created_at":"2026-06-10T01:58:35+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"MERFISH","ontology_term_id":"EFO:0008992"}],"dataset_id":"257adc73-8152-414b-a2c7-73861b8e0c0a","dataset_version_id":"a12f3e3e-4570-4ac7-b0da-0d46f3cbef42","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]}],"description":"A mammalian brain is comprised of numerous cell types organized in an intricate manner to form functional neural circuits. Single-cell RNA sequencing provides a powerful approach to identify cell types based on their gene expression profiles and has revealed many distinct cell populations in the brain. Single-cell epigenomic profiling further provides information on gene-regulatory signatures of different cell types. Understanding how different cell types contribute to brain function, however, requires knowledge of their spatial organization and connectivity, which is not preserved in sequencing-based methods that involve cell dissociation. Here, we used an in situ single-cell transcriptome-imaging method, multiplexed error-robust fluorescence in situ hybridization (MERFISH), to generate a molecularly defined and spatially resolved cell atlas of the mouse primary motor cortex (MOp). We profiled \u223c300,000 cells in the MOp, identified 95 neuronal and non-neuronal cell clusters, and revealed a complex spatial map in which not only excitatory neuronal clusters but also most inhibitory neuronal clusters adopted layered organizations. Notably, intratelencephalic (IT) cells, the largest branch of neurons in the MOp, formed a continuous spectrum of cells with gradual changes in both gene expression profiles and cortical depth positions in a highly correlated manner. Furthermore, we integrated MERFISH with retrograde tracing to probe the projection targets for different MOp neuronal cell types and found that projections of MOp neurons to other cortical regions formed a many-to-many network with each target region receiving input preferentially from a different composition of IT clusters. Overall, our results provide a high-resolution spatial and projection map of molecularly defined cell types in the MOp. We anticipate that the imaging platform described here can be broadly applied to create high-resolution cell atlases of a wide range of systems.","doi":"10.1101/2020.06.04.105700","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ZhuangLab/MERlin"},{"link_name":"Brain Image Library archive","link_type":"RAW_DATA","link_url":"https://download.brainimagelibrary.org/02/26/02265ddb0dae51de/"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://zhuang.harvard.edu/index.html"}],"name":"Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics","published_at":"2021-03-08T22:38:07+00:00","publisher_metadata":{"authors":[{"family":"Zhang","given":"Meng"},{"family":"Eichhorn","given":"Stephen W."},{"family":"Zingg","given":"Brian"},{"family":"Yao","given":"Zizhen"},{"family":"Zeng","given":"Hongkui"},{"family":"Dong","given":"Hongwei"},{"family":"Zhuang","given":"Xiaowei"}],"is_preprint":true,"journal":"bioRxiv","published_at":1591315200.0,"published_day":5,"published_month":6,"published_year":2020},"revised_at":"2026-06-11T16:54:23+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0391c84c-d57d-4741-9277-e4d58f9a3d0c","collection_url":"https://cellxgene.cziscience.com/collections/0391c84c-d57d-4741-9277-e4d58f9a3d0c","collection_version_id":"76143af4-f34e-426f-9caa-8be922f66a06","consortia":[],"contact_email":"andrei.chagin@gu.se","contact_name":"Andrei Chagin","created_at":"2026-06-10T01:24:55+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"cdbff22b-a287-460d-afae-7b497e403491","dataset_version_id":"b6037d0f-c415-45f7-8d01-0e69407fba9c","disease":[{"label":"follicular lymphoma","ontology_term_id":"MONDO:0018906"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"osteoarthritis","ontology_term_id":"MONDO:0005178"},{"label":"primary central nervous system lymphoma","ontology_term_id":"MONDO:0002571"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow cavity","ontology_term_id":"UBERON:0002484","tissue_type":"tissue"}]}],"description":"The bone marrow stroma (BMS) is among the most enigmatic parts of the bone. It contains skeletal stem cells and committed progenitors for the osteo- and adipo-lineages, supports hematopoiesis, and regulates the activity of leukemia cells1,2. Those stromal cells expressing C-X-C-motif-12 chemokine (CXCL12) are unequivocal for hematopoiesis and are often called CXCL12-abundant reticular (CAR) cells3. The microenvironments, or niches where CAR cells are located, determine their functionality4. However, these niches are largely unknown in humans. To fill this gap of knowledge, we developed a tissue-clearing protocol allowing detection and spatial quantification of mRNAs and proteins in sizeable human bone biopsies, named DeepBone and combined it with an atlas of bone marrow single-cell RNA sequencing (scRNAseq) and neuronal network (NN) analysis. CAR cells were found transcriptionally identical to bone marrow mesenchymal stromal cells (BM-MSCs), and all abundantly express CXCL12 chemokine. Spatial analysis revealed that the niches where CXCL12-expressing cells reside were formed by a complex composition of capillaries, sinusoids, adipocytes, and bony trabeculae, and this landscape drastically changed with age. The niche composition was heterogeneous but formed a continuum revealed by unsupervised NN. These insights into spatial organization of the human bone microenvironment will improve our understanding of the mechanisms underlying numerous hematological and bone diseases.","doi":"10.1038/s41467-026-69863-6","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/mcrewcow/Chu_et_al_2023"},{"link_name":"Li et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.7554/eLife.81656"},{"link_name":"Qiu et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.18632/aging.203124"},{"link_name":"Mei et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1186/s13073-023-01272-6"},{"link_name":"Hu et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1136/rmdopen-2022-002314"},{"link_name":"Zhang et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.31083/j.fbl2710295"},{"link_name":"Leimk\u00fchler et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1016/j.stem.2020.11.004"},{"link_name":"Fi\u00e9vet et al.","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.1186/s13287-023-03437-x"}],"name":"Clearing human bone marrow reveals spatial heterogeneity of the stromal niche - Human bone marrow atlas","published_at":"2026-04-30T16:39:24+00:00","publisher_metadata":{"authors":[{"family":"Mov\u00e9rare-Skrtic","given":"Sofia"},{"family":"Nethander","given":"Maria"},{"family":"Li","given":"Lei"},{"family":"Chu","given":"Nelson Tsz Long"},{"family":"Dregval","given":"Ostap"},{"family":"Tian","given":"Xin"},{"family":"Nilsson","given":"Karin H."},{"family":"Henning","given":"Petra"},{"family":"Lerner","given":"Ulf H."},{"family":"Chagin","given":"Andrei S."},{"family":"Ohlsson","given":"Claes"}],"is_preprint":false,"journal":"Nat Commun","published_at":1771632000.0,"published_day":21,"published_month":2,"published_year":2026},"revised_at":"2026-06-11T16:54:26+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"573e2e06-8af0-4d96-bfdd-7d64a4bb9c21","collection_url":"https://cellxgene.cziscience.com/collections/573e2e06-8af0-4d96-bfdd-7d64a4bb9c21","collection_version_id":"0499aa79-8c03-4305-8138-5de10fc778d5","consortia":[],"contact_email":"paula.nieto@cnag.eu","contact_name":"Paula Nieto","created_at":"2025-12-03T22:30:11+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"0bf30b02-db97-4560-b9cd-0fe3588892af","dataset_version_id":"0d240f09-c7d4-4420-89ca-376d19663777","disease":[{"label":"brain cancer","ontology_term_id":"MONDO:0001657"},{"label":"glioblastoma","ontology_term_id":"MONDO:0018177"},{"label":"inflammatory disease","ontology_term_id":"MONDO:0021166"},{"label":"lymphoma","ontology_term_id":"MONDO:0005062"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cerebrospinal fluid","ontology_term_id":"UBERON:0001359","tissue_type":"tissue"}]}],"description":"Single-cell RNA and TCR sequencing of CSF cells across 16 patients and 20 samples, including 4 serial samples of 3 of the patients, suffering from different neurological diseases including lymphoma, brain metastasis, glioblastoma, inflammatory CNS conditions and leptomeningeal disease.","doi":"10.1016/j.xcrm.2026.102651","is_pre_analysis":false,"links":[{"link_name":"GSE286518","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE286518"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/CSF"}],"name":"Immune Response mechanisms in the cerebrospinal fluid in leptomeningeal disease at single cell resolution","published_at":"2025-07-08T19:59:01+00:00","publisher_metadata":{"authors":[{"family":"Nieto","given":"Paula"},{"family":"Klinsing","given":"Svenja"},{"family":"Carat\u00f9","given":"Ginevra"},{"family":"Dettki","given":"Mareike"},{"family":"Marchese","given":"Domenica"},{"family":"Weber","given":"Katharina J."},{"family":"Morabito","given":"Samuel"},{"family":"Lorden","given":"Patricia"},{"family":"Ruano","given":"Irene"},{"family":"Imkeller","given":"Katharina"},{"family":"Velasco","given":"M. Angels"},{"family":"Vidal","given":"Silvia"},{"family":"Melero","given":"Juan L."},{"family":"Euskirchen","given":"Philipp"},{"family":"Czabanka","given":"Marcus"},{"family":"Plate","given":"Karl H."},{"family":"Harter","given":"Patrick N."},{"family":"Pascual-Reguant","given":"Anna"},{"family":"Steinbach","given":"Joachim P."},{"family":"Heyn","given":"Holger"},{"family":"Zeiner","given":"Pia S."},{"family":"Nieto","given":"Juan C."}],"is_preprint":false,"journal":"Cell Reports Medicine","published_at":1772323200.0,"published_day":1,"published_month":3,"published_year":2026},"revised_at":"2026-06-22T18:43:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"350fe77e-cc64-482e-a42a-18bec9e4a629","collection_url":"https://cellxgene.cziscience.com/collections/350fe77e-cc64-482e-a42a-18bec9e4a629","collection_version_id":"2beb4c9e-3d20-46a2-9897-819942c76a61","consortia":[],"contact_email":"michael-stout@omrf.org","contact_name":"Michael B. 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These effects begin to emerge long before follicular exhaustion. Female humans experience a sharp decline in fertility around 35\u2009years of age, which corresponds to declines in oocyte quality. Despite a growing body of work, the field lacks a comprehensive cellular map of the transcriptomic changes in the aging mouse ovary to identify early drivers of ovarian decline. To fill this gap we performed single-cell RNA sequencing on ovarian tissue from young (3-month-old) and reproductively aged (9-month-old) mice. Our analysis revealed a doubling of immune cells in the aged ovary, with lymphocyte proportions increasing the most, which was confirmed by flow cytometry. We also found an age-related downregulation of collagenase pathways in stromal fibroblasts, which corresponds to rises in ovarian fibrosis. Follicular cells displayed stress-response, immunogenic and fibrotic signaling pathway inductions with aging. This report provides critical insights into mechanisms responsible for ovarian aging phenotypes. The data can be explored interactively via a Shiny-based web application.","doi":"10.1038/s43587-023-00552-5","is_pre_analysis":false,"links":[{"link_name":"GSE232309","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE232309"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/StoutLab/OvarianAgingAtlas"},{"link_name":"","link_type":"OTHER","link_url":"https://omrf.shinyapps.io/OvarianAgingSCAtlas/"}],"name":"A single-cell atlas of the aging mouse ovary","published_at":"2024-08-19T18:42:50+00:00","publisher_metadata":{"authors":[{"family":"Isola","given":"Jos\u00e9 V. V."},{"family":"Oca\u00f1as","given":"Sarah R."},{"family":"Hubbart","given":"Chase R."},{"family":"Ko","given":"Sunghwan"},{"family":"Mondal","given":"Samim Ali"},{"family":"Hense","given":"Jessica D."},{"family":"Carter","given":"Hannah N. 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"}]},{"assay":[{"label":"Visium Spatial Gene Expression V1","ontology_term_id":"EFO:0022857"}],"dataset_id":"2cc628d1-b1dd-4300-9cf6-1015e2b1fd3d","dataset_version_id":"36a207de-c1a2-474e-89f0-40117ef9b2e7","disease":[{"label":"triple-negative breast carcinoma","ontology_term_id":"MONDO:0005494"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"}]},{"assay":[{"label":"Visium Spatial Gene Expression V1","ontology_term_id":"EFO:0022857"}],"dataset_id":"10bb68cf-e20b-4c45-a65f-2d7d8129048e","dataset_version_id":"e963ad5f-a05a-48c1-9c31-c9b3da73e00a","disease":[{"label":"triple-negative breast carcinoma","ontology_term_id":"MONDO:0005494"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"}]}],"description":"Breast cancer is one of the most prominent types of cancers, in which therapeutic resistance is a major clinical concern. Specific subtypes, such as claudin-low and metaplastic breast carcinoma (MpBC), have been associated with high nongenetic plasticity, which can facilitate resistance. The similarities and differences between these orthogonal subtypes, identified by molecular and histopathological analyses, respectively, remain insufficiently characterized. Furthermore, adequate methods to identify high-plasticity tumors to better anticipate resistance are lacking. Here, we analyzed 11 triple-negative breast tumors, including 3 claudin-low and 4 MpBC, via high-resolution spatial transcriptomics. We combined pathological annotations and deconvolution approaches to precisely identify tumor spots, on which we performed signature enrichment, differential expression, and copy number analyses. We used The Cancer Genome Atlas and Cancer Cell Line Encyclopedia public databases for external validation of expression markers. By focusing our spatial transcriptomic analyses on tumor cells in MpBC samples, we bypassed the negative impact of stromal contamination and identified specific markers that are neither expressed in other breast cancer subtypes nor expressed in stromal cells. Three markers (BMPER, POPDC3, and SH3RF3) were validated in external expression databases encompassing bulk tumor material and stroma-free cell lines. We unveiled that existing bulk expression signatures of high-plasticity breast cancers are relevant in mesenchymal transdifferentiated compartments but can be hindered by abundant stromal cells in tumor samples, negatively impacting their clinical applicability. Spatial transcriptomic analyses constitute powerful tools to identify specific expression markers and could thus enhance diagnosis and clinical care of rare high-plasticity breast cancers.","doi":"10.1016/j.labinv.2023.100258","is_pre_analysis":false,"links":[{"link_name":"GSE213688","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213688"}],"name":"Spatial Transcriptomics Reveal Pitfalls and Opportunities for the Detection of Rare High-Plasticity Breast Cancer Subtypes","published_at":"2025-02-06T16:35:55+00:00","publisher_metadata":{"authors":[{"family":"Coutant","given":"Ang\u00e8le"},{"family":"Cockenpot","given":"Vincent"},{"family":"Muller","given":"Lauriane"},{"family":"Degletagne","given":"Cyril"},{"family":"Pommier","given":"Roxane"},{"family":"Tonon","given":"Laurie"},{"family":"Ardin","given":"Maude"},{"family":"Michallet","given":"Marie-C\u00e9cile"},{"family":"Caux","given":"Christophe"},{"family":"Laurent","given":"Marie"},{"family":"Morel","given":"Anne-Pierre"},{"family":"Saintigny","given":"Pierre"},{"family":"Puisieux","given":"Alain"},{"family":"Ouzounova","given":"Maria"},{"family":"Martinez","given":"Pierre"}],"is_preprint":false,"journal":"Laboratory Investigation","published_at":1701388800.0,"published_day":1,"published_month":12,"published_year":2023},"revised_at":"2026-06-11T16:54:40+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"f8057c47-fcd8-4fcf-88b0-e2f930080f6e","collection_url":"https://cellxgene.cziscience.com/collections/f8057c47-fcd8-4fcf-88b0-e2f930080f6e","collection_version_id":"68f43ccb-6ab8-450a-a309-1a391441bf10","consortia":[],"contact_email":"mullinsrf@gmail.com","contact_name":"Robert F. Mullins","created_at":"2026-06-10T20:17:21+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"af8b241a-c72c-4470-b1a4-80e7336c6ab6","dataset_version_id":"96d8896a-905d-409a-8cb4-92e1073563ac","disease":[{"label":"age related macular degeneration 7","ontology_term_id":"MONDO:0012419"},{"label":"basal laminar drusen","ontology_term_id":"MONDO:0007472"},{"label":"cataract","ontology_term_id":"MONDO:0005129"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"fovea centralis","ontology_term_id":"UBERON:0001786","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"}]}],"description":"The human retinal pigment epithelium (RPE) and choroid are complex tissues that provide crucial support to the retina. Disease affecting either of these supportive tissues can lead to irreversible blindness in the setting of age-related macular degeneration. In this study, single-cell RNA sequencing was performed on macular and peripheral regions of RPE-choroid from 7 human donor eyes in 2 independent experiments. In the first experiment, total RPE/choroid preparations were evaluated and expression profiles specific to RPE and major choroidal cell populations were identified. As choroidal endothelial cells represent a minority of the total RPE/choroidal cell population but are strongly implicated in age-related macular degeneration (AMD) pathogenesis, a second single-cell RNA-sequencing experiment was performed using endothelial cells enriched by magnetic separation. In this second study, we identified gene expression signatures along the choroidal vascular tree, classifying the transcriptome of human choriocapillaris, arterial, and venous endothelial cells. We found that the choriocapillaris highly and specifically expresses the regulator of cell cycle gene (RGCC), a gene that responds to complement activation and induces apoptosis in endothelial cells. In addition, RGCC was the most up-regulated choriocapillaris gene in a donor diagnosed with AMD. These results provide a characterization of the human RPE and choriocapillaris transcriptome, offering potential insight into the mechanisms of choriocapillaris response to complement injury and choroidal vascular disease in age-related macular degeneration.","doi":"10.1073/pnas.1914143116","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=retinal-pigment-epi"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/7880637a-35a1-4047-b422-b5eac2a2a358"},{"link_name":"GSE135922","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE135922"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-135922"}],"name":"Single-cell transcriptomics of the human retinal pigment epithelium and choroid in health and macular degeneration","published_at":"2022-09-26T08:44:06+00:00","publisher_metadata":{"authors":[{"family":"Voigt","given":"Andrew P."},{"family":"Mulfaul","given":"Kelly"},{"family":"Mullin","given":"Nathaniel K."},{"family":"Flamme-Wiese","given":"Miles J."},{"family":"Giacalone","given":"Joseph C."},{"family":"Stone","given":"Edwin M."},{"family":"Tucker","given":"Budd A."},{"family":"Scheetz","given":"Todd E."},{"family":"Mullins","given":"Robert F."}],"is_preprint":false,"journal":"Proc. Natl. Acad. Sci. U.S.A.","published_at":1574726400.0,"published_day":26,"published_month":11,"published_year":2019},"revised_at":"2026-06-11T16:54:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4cbb929b-b03b-4aa8-a943-00f61dc22641","collection_url":"https://cellxgene.cziscience.com/collections/4cbb929b-b03b-4aa8-a943-00f61dc22641","collection_version_id":"9fb82949-47a2-4576-889f-9a109fb73dd1","consortia":["CZI Cell Science","Human Cell Atlas (HCA)"],"contact_email":"emereu@carrerasresearch.org","contact_name":"Elisabetta Mereu","created_at":"2026-06-09T22:25:39+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"60a29d0b-1a37-4447-ac32-00d701580b47","dataset_version_id":"32b68fe9-ecf9-4302-88e1-c5491e2bc180","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"09b518f9-da64-44cc-aec8-70a89d55611f","dataset_version_id":"46aada24-d005-4486-9e21-866da4fdbd7a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"}]}],"description":"The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3' and 5' scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. \"Horizontal\" integration of scRNA and snRNA-seq improved cell-type identification, while \"vertical\" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.","doi":"10.1101/2025.03.06.637075","is_pre_analysis":false,"links":[],"name":"Multimodal benchmarking dataset for renal cortex characterization (mBDRC)","published_at":"2025-03-27T15:50:41+00:00","publisher_metadata":{"authors":[{"family":"Acera-Mateos","given":"Mario"},{"family":"Adiconis","given":"Xian"},{"family":"Li","given":"Jessica-Kanglin"},{"family":"Marchese","given":"Domenica"},{"family":"Carat\u00f9","given":"Ginevra"},{"family":"Hon","given":"Chung-Chau"},{"family":"Tiwari","given":"Prabha"},{"family":"Kojima","given":"Miki"},{"family":"Vieth","given":"Beate"},{"family":"Murphy","given":"Michael A."},{"family":"Simmons","given":"Sean K."},{"family":"Lefevre","given":"Thomas"},{"family":"Claes","given":"Irene"},{"family":"O\u2019Connor","given":"Christopher L."},{"family":"Menon","given":"Rajasree"},{"family":"Otto","given":"Edgar A."},{"family":"Ando","given":"Yoshinari"},{"family":"Vandereyken","given":"Katy"},{"family":"Kretzler","given":"Matthias"},{"family":"Bitzer","given":"Markus"},{"family":"Fraenkel","given":"Ernest"},{"family":"Voet","given":"Thierry"},{"family":"Enard","given":"Wolfgang"},{"family":"Carninci","given":"Piero"},{"family":"Heyn","given":"Holger"},{"family":"Levin","given":"Joshua Z."},{"family":"Mereu","given":"Elisabetta"}],"is_preprint":true,"journal":"bioRxiv","published_at":1741219200.0,"published_day":6,"published_month":3,"published_year":2025},"revised_at":"2026-06-11T16:54:43+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"886ff63c-af9e-4fcc-9c51-64a92cb6fd48","collection_url":"https://cellxgene.cziscience.com/collections/886ff63c-af9e-4fcc-9c51-64a92cb6fd48","collection_version_id":"fc4c656b-b530-4ec1-97d5-492e6aae1310","consortia":["CZI Neurodegeneration Challenge Network"],"contact_email":"dbergles@jhmi.edu","contact_name":"Dwight Bergles","created_at":"2026-06-10T12:52:46+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0e1c7067-8833-4f54-8847-ad7d33d09c10","dataset_version_id":"dd40284c-50a2-46aa-9d81-26187cba367b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cerebral cortex","ontology_term_id":"UBERON:0000956","tissue_type":"tissue"}]}],"description":"Oligodendrocyte progenitor cells (OPCs) are highly dynamic, widely distributed glial cells of the central nervous system (CNS) that are responsible for generating myelinating oligodendrocytes during development. However, the rates of OPC proliferation and differentiation decline dramatically with aging, which may impair homeostasis, remyelination, and adaptive myelination during learning. To determine how aging influences OPCs, we generated a novel transgenic mouse line that expresses membrane-anchored EGFP under the endogenous promoter/enhancer of Matrilin-4 (Matn4-mEGFP), allowing OPCs to be purified apart from perivascular and mural cells. OPCs isolated from the cerebral cortex of Matn4-mEGFP mice were subjected to single-cell RNA sequencing, providing enhanced resolution of transcriptional changes during key transitions from quiescence to proliferation and differentiation across the lifespan. This Matn4-mEGFP mouse line and single-cell mRNA datasets of cortical OPCs across ages serve as a valuable reference to help define the molecular changes guiding their behavior in various physiological and pathological contexts.","doi":"10.1101/2024.10.27.620502","is_pre_analysis":false,"links":[{"link_name":"GSE249268","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE249268"}],"name":"Transcriptional profiling of murine oligodendrocyte precursor cells across the lifespan","published_at":"2024-11-01T19:48:53+00:00","publisher_metadata":{"authors":[{"family":"Heo","given":"Dongeun"},{"family":"Kim","given":"Anya A."},{"family":"Neumann","given":"Bj\u00f6rn"},{"family":"Doze","given":"Valerie N."},{"family":"Xu","given":"Yu Kang T."},{"family":"Mironova","given":"Yevgeniya A."},{"family":"Slosberg","given":"Jared"},{"family":"Goff","given":"Loyal A."},{"family":"Franklin","given":"Robin J. M."},{"family":"Bergles","given":"Dwight E."}],"is_preprint":true,"journal":"bioRxiv","published_at":1730073600.0,"published_day":28,"published_month":10,"published_year":2024},"revised_at":"2026-06-11T16:54:43+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"625f6bf4-2f33-4942-962e-35243d284837","collection_url":"https://cellxgene.cziscience.com/collections/625f6bf4-2f33-4942-962e-35243d284837","collection_version_id":"b2bb3e91-015d-443c-8acf-fe3c404aca0e","consortia":["LungMAP"],"contact_email":"a5wang@health.ucsd.edu","contact_name":"Allen Wang","created_at":"2026-06-09T22:26:59+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3de0ad6d-4378-4f62-b37b-ec0b75a50d94","dataset_version_id":"92167705-4b81-4c4b-a0b5-abe08910415e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"Large-scale snRNA-seq dataset (46,500 nucle) of the human lung from healthy donors of ~30 weeks, ~3 years and ~30 years of age. Focusing on genes implicated in SARS-CoV-2 cell entry, we observed an increase in the proportion of alveolar epithelial cells expressing ACE2 and TMPRSS2 in adult compared to young lungs. Consistent with expression dynamics, 10 chromatin peaks linked to TMPRSS2 exhibited significantly increased activity with age and harbored IRF and STAT binding sites. Furthermore, we identified 14 common sequence variants in age-increasing peaks with predicted regulatory function, including several associated with respiratory traits and TMPRSS2 expression. Our findings reveal a plausible contributor to why children are more resistant to COVID-19 and provide an epigenomic basis for transferring this resistance to older populations.","doi":"10.7554/eLife.62522","is_pre_analysis":false,"links":[{"link_name":"GSE161382","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161382"},{"link_name":"phs001961","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001961"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/01aacb68-4076-4fd9-9eb9-aba0f48c1b5a"}],"name":"LungMAP \u2014 Human data from a broad age healthy donor group","published_at":"2021-03-16T23:28:52+00:00","publisher_metadata":{"authors":[{"family":"Wang","given":"Allen"},{"family":"Chiou","given":"Joshua"},{"family":"Poirion","given":"Olivier B"},{"family":"Buchanan","given":"Justin"},{"family":"Valdez","given":"Michael J"},{"family":"Verheyden","given":"Jamie M"},{"family":"Hou","given":"Xiaomeng"},{"family":"Kudtarkar","given":"Parul"},{"family":"Narendra","given":"Sharvari"},{"family":"Newsome","given":"Jacklyn M"},{"family":"Guo","given":"Minzhe"},{"family":"Faddah","given":"Dina A"},{"family":"Zhang","given":"Kai"},{"family":"Young","given":"Randee E"},{"family":"Barr","given":"Justinn"},{"family":"Sajti","given":"Eniko"},{"family":"Misra","given":"Ravi"},{"family":"Huyck","given":"Heidie"},{"family":"Rogers","given":"Lisa"},{"family":"Poole","given":"Cory"},{"family":"Whitsett","given":"Jeffery A"},{"family":"Pryhuber","given":"Gloria"},{"family":"Xu","given":"Yan"},{"family":"Gaulton","given":"Kyle J"},{"family":"Preissl","given":"Sebastian"},{"family":"Sun","given":"Xin"},{"name":"NHLBI LungMap Consortium"}],"is_preprint":false,"journal":"eLife","published_at":1604880000.0,"published_day":9,"published_month":11,"published_year":2020},"revised_at":"2026-06-11T16:54:44+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d245b35b-3cc1-4f47-aed6-68dfdadebb5f","collection_url":"https://cellxgene.cziscience.com/collections/d245b35b-3cc1-4f47-aed6-68dfdadebb5f","collection_version_id":"f6523515-a996-4ca1-a522-14b16272de11","consortia":[],"contact_email":"carlo.de_donno@roche.com","contact_name":"Carlo De Donno","created_at":"2026-06-10T04:47:17+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"b2370cf4-e517-45c6-be54-f2c1c64b117f","dataset_version_id":"2372d9bd-7337-4c92-b078-05a0bc08a1e8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"hippocampal formation","ontology_term_id":"UBERON:0002421","tissue_type":"tissue"}]}],"description":"This dataset presents a comprehensive single-cell transcriptomic profile of the adult male mouse hippocampus under baseline and acute social stress conditions. It includes both wild-type and genetically modified mouse lines with conditional knockouts for glucocorticoid (GR) and mineralocorticoid (MR) receptors. The main objective was to map the cell-type-specific transcriptional landscape of the hippocampus, identify gene expression changes induced by acute social stress, and examine the role of GR and MR receptors in the stress response across specific neuronal populations. Biological samples consisted of 36 adult male C57BL/6 mice. After quality control, 34 samples were retained, comprising a total of 125,896 single cells for downstream analysis. Mice were assigned to either a control or stress condition. Control mice were single-housed in a novel cage for five hours. Stressed mice underwent acute social defeat by exposure to an aggressive CD1 mouse, followed by continued sensory exposure (sight, sound, and smell) for five hours using a perforated barrier.\n\nThe dataset includes both wild-type animals and conditional knockouts. Wild-type mice were GR^flox/flox or MR^flox/flox littermates. Knockout models were generated using two Cre driver lines: Nex-Cre for glutamatergic neuron-specific knockout and Dlx5/6-Cre for GABAergic neuron-specific knockout. This yielded four knockout lines: GR^Nex, GR^Dlx, MR^Nex, and MR^Dlx. The Nex-Cre promoter is under the control of the Neurod6 gene, which is not expressed in the adult dentate gyrus of the hippocampus. As there is no Cre expression in the dentate gyrus in GR^Nex and MR^Nex mouse lines, neither GR nor MR were deleted in this hippocampal subregion. Each condition was replicated in triplicate per genotype and treatment, with six mice per group. Tissue was harvested five hours after the stress or control exposure to capture gene expression changes beyond immediate early gene responses. The posterior hippocampus was dissected and processed for single-cell RNA sequencing.","doi":"10.1038/s41380-025-03417-y","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/theislab/MRGR_stress_analysis"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://zenodo.org/records/15213233"}],"name":"Single-cell characterization of the adult male hippocampus suggests a prominent, and cell-type specific, role for Nrgn and Sgk1 in response to a social stressor","published_at":"2026-04-24T21:46:20+00:00","publisher_metadata":{"authors":[{"family":"De Donno","given":"Carlo"},{"family":"Lopez","given":"Juan Pablo"},{"family":"Luecken","given":"Malte D."},{"family":"Kos","given":"Aron"},{"family":"Brivio","given":"Elena"},{"family":"Bordes","given":"Joeri"},{"family":"Yang","given":"Huanqing"},{"family":"Deussing","given":"Jan M."},{"family":"Schmidt","given":"Mathias V."},{"family":"Theis","given":"Fabian J."},{"family":"Chen","given":"Alon"}],"is_preprint":false,"journal":"Mol Psychiatry","published_at":1772323200.0,"published_day":1,"published_month":3,"published_year":2026},"revised_at":"2026-06-11T16:54:45+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"b1a879f6-5638-48d3-8f64-f6592c1b1561","collection_url":"https://cellxgene.cziscience.com/collections/b1a879f6-5638-48d3-8f64-f6592c1b1561","collection_version_id":"d8856f5e-149a-431e-bb62-3cd32f6b76c8","consortia":["CZI Cell Science","Wellcome HCA Strategic Science Support"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. 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developing immune system as a distributed network across tissues. We profiled nine prenatal tissues combining single-cell RNA sequencing, antigen-receptor sequencing, and spatial transcriptomics to reconstruct the developing human immune system. This revealed the late acquisition of immune-effector functions by myeloid and lymphoid cell subsets and the maturation of monocytes and T cells before peripheral tissue seeding. Moreover, we uncovered system-wide blood and immune cell development beyond primary hematopoietic organs, characterized human prenatal B1 cells, and shed light on the origin of unconventional T cells. Our atlas provides both valuable data resources and biological insights that will facilitate cell engineering, regenerative medicine, and disease understanding.","doi":"10.1126/science.abo0510","is_pre_analysis":false,"links":[{"link_name":"scVI Models","link_type":"DATA_SOURCE","link_url":"https://developmental.cellatlas.io/fetal-immune"},{"link_name":"Teichmann Lab","link_type":"LAB_WEBSITE","link_url":"http://www.teichlab.org/"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=fetal-immune"},{"link_name":"E-MTAB-11343","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11343"},{"link_name":"Data processing and analysis scripts","link_type":"OTHER","link_url":"https://github.com/Teichlab/Pan_fetal_immune"},{"link_name":"PSC-ATO protocol","link_type":"PROTOCOL","link_url":"https://doi.org/10.1016/j.stem.2018.12.011"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/fcaa53cd-ba57-4bfe-af9c-eaa958f95c1a"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1843"},{"link_name":"E-MTAB-11341","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11341"}],"name":"Mapping the developing human immune system across organs","published_at":"2022-10-04T23:05:32+00:00","publisher_metadata":{"authors":[{"family":"Suo","given":"Chenqu"},{"family":"Dann","given":"Emma"},{"family":"Goh","given":"Issac"},{"family":"Jardine","given":"Laura"},{"family":"Kleshchevnikov","given":"Vitalii"},{"family":"Park","given":"Jong-Eun"},{"family":"Botting","given":"Rachel A."},{"family":"Stephenson","given":"Emily"},{"family":"Engelbert","given":"Justin"},{"family":"Tuong","given":"Zewen Kelvin"},{"family":"Polanski","given":"Krzysztof"},{"family":"Yayon","given":"Nadav"},{"family":"Xu","given":"Chuan"},{"family":"Suchanek","given":"Ondrej"},{"family":"Elmentaite","given":"Rasa"},{"family":"Dom\u00ednguez Conde","given":"Cecilia"},{"family":"He","given":"Peng"},{"family":"Pritchard","given":"Sophie"},{"family":"Miah","given":"Mohi"},{"family":"Moldovan","given":"Corina"},{"family":"Steemers","given":"Alexander S."},{"family":"Mazin","given":"Pavel"},{"family":"Prete","given":"Martin"},{"family":"Horsfall","given":"Dave"},{"family":"Marioni","given":"John C."},{"family":"Clatworthy","given":"Menna R."},{"family":"Haniffa","given":"Muzlifah"},{"family":"Teichmann","given":"Sarah A."}],"is_preprint":false,"journal":"Science","published_at":1654214400.0,"published_day":3,"published_month":6,"published_year":2022},"revised_at":"2026-06-11T16:54:47+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9c9ce98a-6b02-4262-9407-1ebb2de31f63","collection_url":"https://cellxgene.cziscience.com/collections/9c9ce98a-6b02-4262-9407-1ebb2de31f63","collection_version_id":"2e620e36-21f6-41bb-8770-bc79c6b6ec3e","consortia":[],"contact_email":"jfmartin@bcm.edu","contact_name":"James F. 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With current therapies, more than 90% of CHD patients survive into adulthood but often suffer premature death from heart failure (HF) and non-cardiac causes 1. To gain insight into poorly understood disease progression, we performed single nuclear RNA sequencing (snRNA-seq) and analyzed 157,273 nuclei from donors and CHD patients, including hypoplastic left heart syndrome (HLHS) and Tetralogy of Fallot (TOF), two common forms of cyanotic CHD lesions, as well as, dilated (DCM) and hypertrophic (HCM) cardiomyopathies. We observed CHD specific cell states in cardiomyocytes (CMs) which had evidence of insulin resistance and increased FOXO and CRIM1 expression. Cardiac fibroblasts (CFs) in HLHS had enrichment for a low HIPPO and high YAP cell state characteristic of activated CFs. Imaging Mass Cytometry (IMC) uncovered the spatially resolved perivascular microenvironment consistent with an immunodeficient state in CHD. Peripheral immune cell profiling suggested deficient monocytic immunity in CHD in agreement with CHD predilection to infection and cancer 2. Our comprehensive CHD phenotyping provides a roadmap for future personalized medicine in CHD.","doi":"10.1038/s41586-022-04989-3","is_pre_analysis":false,"links":[{"link_name":"GSE203275","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE203275"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.jfmartinlab.com/"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1852/integrated-multiomic-characterization-of-congenital-heart-disease#study-summary"}],"name":"Integrated multi-omic characterization of congenital heart disease","published_at":"2026-05-01T17:47:50+00:00","publisher_metadata":{"authors":[{"family":"Hill","given":"Matthew C."},{"family":"Kadow","given":"Zachary A."},{"family":"Long","given":"Hali"},{"family":"Morikawa","given":"Yuka"},{"family":"Martin","given":"Thomas J."},{"family":"Birks","given":"Emma J."},{"family":"Campbell","given":"Kenneth S."},{"family":"Nerbonne","given":"Jeanne"},{"family":"Lavine","given":"Kory"},{"family":"Wadhwa","given":"Lalita"},{"family":"Wang","given":"Jun"},{"family":"Turaga","given":"Diwakar"},{"family":"Adachi","given":"Iki"},{"family":"Martin","given":"James F."}],"is_preprint":false,"journal":"Nature","published_at":1659571200.0,"published_day":4,"published_month":8,"published_year":2022},"revised_at":"2026-06-11T16:54:50+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2a9a17c9-1f61-4877-b384-b8cd5ffa4085","collection_url":"https://cellxgene.cziscience.com/collections/2a9a17c9-1f61-4877-b384-b8cd5ffa4085","collection_version_id":"fcf7dce6-531f-471b-8611-179ff9ab00d2","consortia":["CZ Biohub"],"contact_email":"thsuanwu@stanford.edu","contact_name":"Timothy Wu","created_at":"2026-06-10T08:40:19+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7f7faf6b-f11d-4f07-bc1c-188a4472748d","dataset_version_id":"ffb8fb3b-be0f-429f-8323-621473e8d352","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"upper lobe of left lung","ontology_term_id":"UBERON:0008952","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7c497c66-c2e2-4291-8b96-339e5e65f314","dataset_version_id":"1c83edae-640c-4eeb-994f-1b32af63506d","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"upper lobe of left lung","ontology_term_id":"UBERON:0008952","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7b55fe5c-d5c8-48e0-a1a3-54c5b9074f3f","dataset_version_id":"2278cb86-c314-4e81-bcb5-66c76aec24a1","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lower lobe of left lung","ontology_term_id":"UBERON:0008953","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"2ac76f1b-43ef-4271-8686-2f165570989f","dataset_version_id":"0f476931-bff3-49fc-868f-8885e0a163a6","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"upper lobe of left lung","ontology_term_id":"UBERON:0008952","tissue_type":"tissue"}]}],"description":"Early stages of deadly respiratory diseases such as COVID-19 have been challenging to elucidate due to the lack of an experimental system that recapitulates the cellular and structural complexity of the human lung, while\u00a0allowing precise control over disease initiation and systematic interrogation of molecular events at cellular resolution. We show that droplet-based single cell RNA sequencing of healthy human lung slices cultured ex vivo\u00a0productively infected with SARS-CoV-2 can distinguish the cellular identities of ~384,000 human lung cells distributed across the major tissue compartments and define the cellular tropism of the virus and its distinct effects\u00a0on host cell gene expression.","doi":"10.1084/jem.20232192","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://www.synapse.org/#!Synapse:syn53694312"},{"link_name":"PRJNA847631","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA847631"}],"name":"A molecular cell atlas of COVID-19 initiation in human lung","published_at":"2024-08-07T20:47:46+00:00","publisher_metadata":{"authors":[{"family":"Wu","given":"Timothy Ting-Hsuan"},{"family":"Travaglini","given":"Kyle J."},{"family":"Rustagi","given":"Arjun"},{"family":"Xu","given":"Duo"},{"family":"Zhang","given":"Yue"},{"family":"Andronov","given":"Leonid"},{"family":"Jang","given":"SoRi"},{"family":"Gillich","given":"Astrid"},{"family":"Dehghannasiri","given":"Roozbeh"},{"family":"Mart\u00ednez-Col\u00f3n","given":"Giovanny J."},{"family":"Beck","given":"Aimee"},{"family":"Liu","given":"Daniel Dan"},{"family":"Wilk","given":"Aaron J."},{"family":"Morri","given":"Maurizio"},{"family":"Trope","given":"Winston L."},{"family":"Bierman","given":"Rob"},{"family":"Weissman","given":"Irving L."},{"family":"Shrager","given":"Joseph B."},{"family":"Quake","given":"Stephen R."},{"family":"Kuo","given":"Christin S."},{"family":"Salzman","given":"Julia"},{"family":"Moerner","given":"W.E."},{"family":"Kim","given":"Peter S."},{"family":"Blish","given":"Catherine A."},{"family":"Krasnow","given":"Mark A."}],"is_preprint":false,"journal":"Journal of Experimental Medicine","published_at":1717372800.0,"published_day":3,"published_month":6,"published_year":2024},"revised_at":"2026-06-11T16:54:51+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"6d203948-a779-4b69-9b3f-1ee1dadc3980","collection_url":"https://cellxgene.cziscience.com/collections/6d203948-a779-4b69-9b3f-1ee1dadc3980","collection_version_id":"baa82068-cb5d-4682-beea-51c6e22285db","consortia":["CZI Cell Science"],"contact_email":"bogi@hs.uci.edu","contact_name":"Bogi Andersen","created_at":"2026-06-10T16:45:53+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f1f123cc-ca2c-460f-b7f1-88240efb1e82","dataset_version_id":"9662b6de-67f5-4698-a0e6-e376787a7b68","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"skin epidermis","ontology_term_id":"UBERON:0001003","tissue_type":"tissue"},{"label":"skin of body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"de94c504-4b58-4f42-b68d-74a8e4892f0e","dataset_version_id":"19292dfa-1aa8-43be-966f-4172977141e0","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dermis","ontology_term_id":"UBERON:0002067","tissue_type":"tissue"},{"label":"skin epidermis","ontology_term_id":"UBERON:0001003","tissue_type":"tissue"},{"label":"skin of body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"da684768-fb01-455b-9f0f-b63a3e2f844f","dataset_version_id":"99c00c97-629f-49a4-9b3b-46a930a6d09d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dermis","ontology_term_id":"UBERON:0002067","tissue_type":"tissue"},{"label":"skin of body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"}]}],"description":"Palmoplantar skin is structurally and functionally unique, but the transcriptional programs driving this specialization are unclear. Here, we use bulk and single-cell RNA sequencing of human palm, sole, and hip skin to describe the distinguishing characteristics of palmoplantar and non-palmoplantar skin while also uncovering differences between palmar and plantar sites. Our approach reveals an altered immune environment in palmoplantar skin, with downregulation of diverse immunological processes and decreased immune cell populations. Further, we identify specific fibroblast populations that appear to orchestrate key differences in cell-cell communication in palm, sole, and hip. Dedicated keratinocyte analysis highlights major differences in basal cell fraction among the three sites and demonstrates the existence of two spinous keratinocyte populations constituting parallel, site-selective epidermal differentiation trajectories. In summary, this deep characterization of highly adapted palmoplantar skin contributes key insights into the fundamental biology of human skin and provides a valuable data resource for further investigation.","doi":"10.1016/j.celrep.2023.111994","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://www.skingenes.org/"},{"link_name":"GSE202352","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE202352"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/da74b507-60ee-4dd1-bd02-807bb051a337"}],"name":"Differential cell composition and split epidermal differentiation in human palm, sole, and hip skin","published_at":"2023-05-10T15:59:20+00:00","publisher_metadata":{"authors":[{"family":"Wiedemann","given":"Julie"},{"family":"Billi","given":"Allison C."},{"family":"Bocci","given":"Federico"},{"family":"Kashgari","given":"Ghaidaa"},{"family":"Xing","given":"Enze"},{"family":"Tsoi","given":"Lam C."},{"family":"Meller","given":"Leo"},{"family":"Swindell","given":"William R."},{"family":"Wasikowski","given":"Rachael"},{"family":"Xing","given":"Xianying"},{"family":"Ma","given":"Feiyang"},{"family":"Gharaee-Kermani","given":"Mehrnaz"},{"family":"Kahlenberg","given":"J. 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Yet, the molecular features associated with DA neuron vulnerability have not yet been fully identified. To comprehensively characterize nigral DA neuron types and their relative vulnerabilities to PD, we developed a protocol to enrich and transcriptionally profile thousands of DA neurons from PD patients and matched controls, sampling a total of 387,483 nuclei, including 22,048 DA neuron profiles. We identified 10 populations and spatially localized each within the SNpc using Slide-seq. A single subtype, marked by the expression of the gene AGTR1 and spatially confined to the ventral tier of SNpc, was highly susceptible to loss and showed the strongest upregulation of targets of TP53 and NR2F2, nominating molecular processes associated with degeneration in vivo. This same vulnerable population was specifically enriched for the heritable risk associated with PD, highlighting the importance of cell-intrinsic pathways in determining the differential vulnerability of DA neurons to PD-associated degeneration. NB: For performing gene searches, all gene names have been capitalized.","doi":"10.1038/s41593-022-01061-1","is_pre_analysis":false,"links":[{"link_name":"singlecell.broadinstitute.org","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1768/"},{"link_name":"macoskolab.com","link_type":"LAB_WEBSITE","link_url":"https://macoskolab.com/"},{"link_name":"GSE178265","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178265"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/c412be53-cf95-47c7-980c-c0a0caa2d3a0"}],"name":"Single-cell genomic profiling of human dopamine neurons identifies a population that selectively degenerates in Parkinson\u2019s disease","published_at":"2023-10-03T03:48:53+00:00","publisher_metadata":{"authors":[{"family":"Kamath","given":"Tushar"},{"family":"Abdulraouf","given":"Abdulraouf"},{"family":"Burris","given":"S. 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Although cell types are largely stable throughout the lifespan, altered transcriptional and epigenetic regulation may contribute to cognitive changes with advanced age. Using single nucleus multiomic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex samples from young adult and aged donors, we found widespread age- and sex-related variability in specific neuronal cell types. The proportion of GABAergic inhibitory cells, including SST and VIP expressing cells, was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation compared with inhibitory cells. Hundreds of genes involved in synaptic activity were downregulated, while genes located in subtelomeric regions were upregulated with age. We further mapped sex differences in autosomal gene expression and escape from X-inactivation in specific neuron types. Multiomic single nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.","doi":"10.1016/j.neuron.2024.05.013","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/snmcat-v1-n92ld914xg5b/v1"}],"name":"Neuron type-specific effects of human aging and sex on DNA methylation and transcription","published_at":"2023-11-11T01:02:44+00:00","publisher_metadata":{"authors":[{"family":"Chien","given":"Jo-Fan"},{"family":"Liu","given":"Hanqing"},{"family":"Wang","given":"Bang-An"},{"family":"Luo","given":"Chongyuan"},{"family":"Bartlett","given":"Anna"},{"family":"Castanon","given":"Rosa"},{"family":"Johnson","given":"Nicholas D."},{"family":"Nery","given":"Joseph R."},{"family":"Osteen","given":"Julia"},{"family":"Li","given":"Junhao"},{"family":"Altshul","given":"Jordan"},{"family":"Kenworthy","given":"Mia"},{"family":"Valadon","given":"Cynthia"},{"family":"Liem","given":"Michelle"},{"family":"Claffey","given":"Naomi"},{"family":"O'Connor","given":"Carolyn"},{"family":"Seeker","given":"Luise A."},{"family":"Ecker","given":"Joseph R."},{"family":"Behrens","given":"M. 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In this study, we systematically mapped the molecular, cellular and spatial composition of human fetal cerebellum by combining laser capture microscopy and SPLiT-seq single-nucleus transcriptomics. We profiled functionally distinct regions and gene expression dynamics within cell types and across development. The resulting cell atlas demonstrates that the molecular organization of the cerebellar anlage recapitulates cytoarchitecturally distinct regions and developmentally transient cell types that are distinct from the mouse cerebellum. By mapping genes dominant for pediatric and adult neurological disorders onto our dataset, we identify relevant cell types underlying disease mechanisms. These data provide a resource for probing the cellular basis of human cerebellar development and disease.","doi":"10.1038/s41593-021-00872-y","is_pre_analysis":false,"links":[{"link_name":"Sequence data (phs001908.v2.p1)","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001908"},{"link_name":"UCSC Cell Browser","link_type":"OTHER","link_url":"https://cbl-dev.cells.ucsc.edu/"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/85a9263b-0887-48ed-ab1a-ddfa773727b6"}],"name":"Spatial and cell type transcriptional landscape of human cerebellar development","published_at":"2023-08-31T01:23:39+00:00","publisher_metadata":{"authors":[{"family":"Aldinger","given":"Kimberly A."},{"family":"Thomson","given":"Zachary"},{"family":"Phelps","given":"Ian G."},{"family":"Haldipur","given":"Parthiv"},{"family":"Deng","given":"Mei"},{"family":"Timms","given":"Andrew E."},{"family":"Hirano","given":"Matthew"},{"family":"Santpere","given":"Gabriel"},{"family":"Roco","given":"Charles"},{"family":"Rosenberg","given":"Alexander B."},{"family":"Lorente-Galdos","given":"Belen"},{"family":"Gulden","given":"Forrest O."},{"family":"O\u2019Day","given":"Diana"},{"family":"Overman","given":"Lynne M."},{"family":"Lisgo","given":"Steven N."},{"family":"Alexandre","given":"Paula"},{"family":"Sestan","given":"Nenad"},{"family":"Doherty","given":"Dan"},{"family":"Dobyns","given":"William B."},{"family":"Seelig","given":"Georg"},{"family":"Glass","given":"Ian A."},{"family":"Millen","given":"Kathleen J."}],"is_preprint":false,"journal":"Nat Neurosci","published_at":1627776000.0,"published_day":1,"published_month":8,"published_year":2021},"revised_at":"2026-06-11T16:54:59+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"10ec9198-584e-4a7e-8a24-4a332915a4ef","collection_url":"https://cellxgene.cziscience.com/collections/10ec9198-584e-4a7e-8a24-4a332915a4ef","collection_version_id":"dbf04ad1-070f-41f7-9464-fea81a0808fd","consortia":["Human Tumor Atlas Network (HTAN)"],"contact_email":"chenc6@email.chop.edu","contact_name":"Changya Chen","created_at":"2026-06-10T17:31:12+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"cf83c98a-3791-4537-bbde-a719f6d73c13","dataset_version_id":"0607fd1a-a1b1-44e4-82f5-9c6d9f8e68b5","disease":[{"label":"B-cell acute lymphoblastic leukemia","ontology_term_id":"MONDO:0004947"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"738942eb-ac72-44ff-a64b-8943b5ecd8d9","dataset_version_id":"7fa2c044-4581-4a36-9373-8e7e563ad6d6","disease":[{"label":"B-cell acute lymphoblastic leukemia","ontology_term_id":"MONDO:0004947"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"This dataset comprises 18 infant KMT2A-r B-cell acute lymphoblastic leukemia (B-ALL) samples and 5 samples from healthy bone marrow donors. We sequenced a total 128588 cells from 18 patients and 33,824 cells from healthy donors (total: 162,412). We utilized this dataset to investigate age-specific differences and identify the key drivers response for the adverse clinical outcomes in infant KMT2A-r B-ALL.","doi":"10.1182/blood.2021013442","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/tanlabcode/KMT2Ar_Paper"},{"link_name":"","link_type":"OTHER","link_url":"https://humantumoratlas.org/explore"},{"link_name":"phs002371","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002371"}],"name":"HTAN-CHOP - Single-cell multiomics reveals increased plasticity, resistant populations, and stem-cell\u2013like blasts in KMT2A-rearranged leukemia","published_at":"2023-10-18T17:05:47+00:00","publisher_metadata":{"authors":[{"family":"Chen","given":"Changya"},{"family":"Yu","given":"Wenbao"},{"family":"Alikarami","given":"Fatemeh"},{"family":"Qiu","given":"Qi"},{"family":"Chen","given":"Chia-hui"},{"family":"Flournoy","given":"Jennifer"},{"family":"Gao","given":"Peng"},{"family":"Uzun","given":"Yasin"},{"family":"Fang","given":"Li"},{"family":"Davenport","given":"James W."},{"family":"Hu","given":"Yuxuan"},{"family":"Zhu","given":"Qin"},{"family":"Wang","given":"Kai"},{"family":"Libbrecht","given":"Clara"},{"family":"Felmeister","given":"Alex"},{"family":"Rozich","given":"Isaiah"},{"family":"Ding","given":"Yang-yang"},{"family":"Hunger","given":"Stephen P."},{"family":"Felix","given":"Carolyn A."},{"family":"Wu","given":"Hao"},{"family":"Brown","given":"Patrick A."},{"family":"Guest","given":"Erin M."},{"family":"Barrett","given":"David M."},{"family":"Bernt","given":"Kathrin M."},{"family":"Tan","given":"Kai"}],"is_preprint":false,"journal":"Blood","published_at":1649289600.0,"published_day":7,"published_month":4,"published_year":2022},"revised_at":"2026-06-11T16:55:00+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"125eef58-0f61-4963-9b08-53e851ab65fb","collection_url":"https://cellxgene.cziscience.com/collections/125eef58-0f61-4963-9b08-53e851ab65fb","collection_version_id":"69955443-63b7-456d-8c8c-f8f6a4ac8166","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"my4@sanger.ac.uk","contact_name":"Matthew Young","created_at":"2026-06-10T10:33:28+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"105c7dad-0468-4628-a5be-2bb42c6a8ae4","dataset_version_id":"b3831acc-a883-4564-b90f-18e53c6e7232","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"kidney blood vessel","ontology_term_id":"UBERON:0003517","tissue_type":"tissue"},{"label":"renal medulla","ontology_term_id":"UBERON:0000362","tissue_type":"tissue"},{"label":"renal pelvis","ontology_term_id":"UBERON:0001224","tissue_type":"tissue"}]}],"description":"Understanding tumor origins and the similarities and differences between organ-specific cancers is important for determining treatment options. Young et al. generated more than 72,000 single-cell transcriptomes from healthy and cancerous human kidneys. From these data, they determined that Wilms tumor, a pediatric kidney cancer, originates from aberrant fetal cells, whereas adult kidney cancers are likely derived from a specific subtype of proximal convoluted tubular cell.","doi":"10.1126/science.aat1699","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/constantAmateur/scKidneyTumors"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001002325"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001002553"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001002486"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001002171"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/d8ae869c-39c2-4cdd-b3fc-2d0d8f60e7b8"}],"name":"Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors","published_at":"2022-03-25T14:14:24+00:00","publisher_metadata":{"authors":[{"family":"Young","given":"Matthew D."},{"family":"Mitchell","given":"Thomas J."},{"family":"Vieira Braga","given":"Felipe A."},{"family":"Tran","given":"Maxine G. B."},{"family":"Stewart","given":"Benjamin J."},{"family":"Ferdinand","given":"John R."},{"family":"Collord","given":"Grace"},{"family":"Botting","given":"Rachel A."},{"family":"Popescu","given":"Dorin-Mirel"},{"family":"Loudon","given":"Kevin W."},{"family":"Vento-Tormo","given":"Roser"},{"family":"Stephenson","given":"Emily"},{"family":"Cagan","given":"Alex"},{"family":"Farndon","given":"Sarah J."},{"family":"Del Castillo Velasco-Herrera","given":"Martin"},{"family":"Guzzo","given":"Charlotte"},{"family":"Richoz","given":"Nathan"},{"family":"Mamanova","given":"Lira"},{"family":"Aho","given":"Tevita"},{"family":"Armitage","given":"James N."},{"family":"Riddick","given":"Antony C. P."},{"family":"Mushtaq","given":"Imran"},{"family":"Farrell","given":"Stephen"},{"family":"Rampling","given":"Dyanne"},{"family":"Nicholson","given":"James"},{"family":"Filby","given":"Andrew"},{"family":"Burge","given":"Johanna"},{"family":"Lisgo","given":"Steven"},{"family":"Maxwell","given":"Patrick H."},{"family":"Lindsay","given":"Susan"},{"family":"Warren","given":"Anne Y."},{"family":"Stewart","given":"Grant D."},{"family":"Sebire","given":"Neil"},{"family":"Coleman","given":"Nicholas"},{"family":"Haniffa","given":"Muzlifah"},{"family":"Teichmann","given":"Sarah A."},{"family":"Clatworthy","given":"Menna"},{"family":"Behjati","given":"Sam"}],"is_preprint":false,"journal":"Science","published_at":1533859200.0,"published_day":10,"published_month":8,"published_year":2018},"revised_at":"2026-06-11T16:55:01+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e276e3e2-197a-4524-abd1-a753a48dc33a","collection_url":"https://cellxgene.cziscience.com/collections/e276e3e2-197a-4524-abd1-a753a48dc33a","collection_version_id":"48fee413-a6d9-41fe-9a7f-c8550bdb5ca2","consortia":[],"contact_email":"Don.Hayes@cchmc.org","contact_name":"Don Hayes","created_at":"2026-06-10T16:17:03+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"10c0c666-bd99-4a5c-b697-f1be835f5427","dataset_version_id":"af6e81be-e65c-4821-987e-e0eb6c8acd59","disease":[{"label":"acute graft versus host disease","ontology_term_id":"MONDO:0020546"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"Rationale\nAcute cellular rejection (ACR) remains a significant challenge in lung transplantation, with incomplete understanding of its molecular mechanisms and pathways linking ACR to chronic lung allograft dysfunction (CLAD).\nObjectives\nTo characterize the cellular and molecular mechanisms underlying ACR in lung allografts using single cell genomics and identify potential therapeutic targets for CLAD.\nMethods\nSingle cell RNA-sequencing of freshly collected lung tissue was performed across 8 pediatric and adult patients with ACR, Resolved ACR, and surveillance biopsies without ACR. Validation included gene microarray analysis, immunofluorescence, and single cell ATAC-seq.\nMeasurements and Main Results\nGene set enrichment analysis revealed persistent TGF-\u03b2 signaling and PI3K/AKT/mTOR pathway activation in both ACR and Resolved samples, validated by immunofluorescence showing sustained elevation of mTOR activation marker phosphorylated-S6 ribosomal protein and COL3A1. Fibrogenic cells exhibited myofibroblast gene signatures via mesenchymal state transitions rather than epithelial- or endothelial-to-mesenchymal transition. Cell communication analysis showed increased Type II Interferon signaling, with Jak/Stat pathway activation in endothelial and basal cells, and reduced VE-Cadherin staining in ACR. Compositional analysis revealed increased cytotoxic, memory T cells and dendritic cells, with persistent reduction of natural killer cells in ACR and Resolved. Donor/recipient analysis revealed predominantly recipient-derived immune cells in ACR.\nConclusions\nPersistent TGF-\u03b2 and mTOR pathway activation following histologic ACR resolution provides molecular insight into ACR-CLAD linkage and suggests mTOR inhibition and TGF-\u03b2 blockade as potential therapeutic mechanisms to prevent CLAD.","doi":"10.1016/j.healun.2026.02.1666","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://lungallomap.net/"},{"link_name":"GSE274199","link_type":"DATA_SOURCE","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274199"}],"name":"Human Lung Allografts Experience Persistent Fibrogenic Shift Following Acute Cellular Rejection","published_at":"2026-02-27T18:10:28+00:00","publisher_metadata":{"authors":[{"family":"Potter","given":"Andrew S."},{"family":"Sharma","given":"Nirmal S."},{"family":"Goda","given":"Yasufumi"},{"family":"Patel","given":"Kapil N."},{"family":"Qureshi","given":"Muhammad R."},{"family":"Halloran","given":"Kieran"},{"family":"Halloran","given":"Philip F."},{"family":"Wallace","given":"Carolyn"},{"family":"Ashfaq","given":"Awais"},{"family":"Morales","given":"David L.S."},{"family":"Hayes","given":"Don"}],"is_preprint":false,"journal":"The Journal of Heart and Lung Transplantation","published_at":1782864000.0,"published_day":1,"published_month":7,"published_year":2026},"revised_at":"2026-06-11T16:55:04+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4d74781b-8186-4c9a-b659-ff4dc4601d91","collection_url":"https://cellxgene.cziscience.com/collections/4d74781b-8186-4c9a-b659-ff4dc4601d91","collection_version_id":"d1d6a138-be6c-44cb-adc6-f3100eac1cd3","consortia":["CZI Cell Science"],"contact_email":"km16@sanger.ac.uk","contact_name":"Kerstin B. Meyer","created_at":"2026-06-10T23:25:27+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"b07fb54c-d7ad-4995-8bb0-8f3d8611cabe","dataset_version_id":"8bb3a141-127f-4cee-9b4e-c32cde955f67","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"epithelium of esophagus","ontology_term_id":"UBERON:0001976","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"644a578d-ffdc-446b-9679-e7ab4c919c13","dataset_version_id":"7e526bde-0076-4293-9cb9-ed23a7e9e83b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"spleen","ontology_term_id":"UBERON:0002106","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"2672b679-8048-4f5e-9786-f1b196ccfd08","dataset_version_id":"60c74b40-321d-4df4-a507-bdd139a22cde","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung parenchyma","ontology_term_id":"UBERON:0008946","tissue_type":"tissue"}]}],"description":"The Human Cell Atlas is a large international collaborative effort to map all cell types of the human body. Single-cell RNA sequencing can generate high-quality data for the delivery of such an atlas. However, delays between fresh sample collection and processing may lead to poor data and difficulties in experimental design.\n\nThis study assesses the effect of cold storage on fresh healthy spleen, esophagus, and lung from \u2265\u20095 donors over 72\u2009h. We collect 240,000 high-quality single-cell transcriptomes with detailed cell type annotations and whole genome sequences of donors, enabling future eQTL studies. Our data provide a valuable resource for the study of these 3 organs and will allow cross-organ comparison of cell types.\n\nWe see little effect of cold ischemic time on cell yield, total number of reads per cell, and other quality control metrics in any of the tissues within the first 24\u2009h. However, we observe a decrease in the proportions of lung T cells at 72\u2009h, higher percentage of mitochondrial reads, and increased contamination by background ambient RNA reads in the 72-h samples in the spleen, which is cell type specific.\n\nIn conclusion, we present robust protocols for tissue preservation for up to 24\u2009h prior to scRNA-seq analysis. This greatly facilitates the logistics of sample collection for Human Cell Atlas or clinical studies since it increases the time frames for sample processing.","doi":"10.1186/s13059-019-1906-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=tissue-stability"},{"link_name":"CGAP MACS Live Dead Separation","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cgap-macs-live-dead-separation-dm6gp71jgzpn/v1"},{"link_name":"CGAP Human Spleen Dissociation, Tissue Stability Study","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cgap-human-spleen-dissociation-tissue-stability-st-ewov1yb92vr2/v1"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"http://www.tissuestabilitycellatlas.org/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/c4077b3c-5c98-4d26-a614-246d12c2e5d7"},{"link_name":"CGAP Human Lung Dissociation - Tissue Stability Study","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cgap-human-lung-dissociation-tissue-stability-stud-5jyl8noe7l2w/v1"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/elo073/TissStab"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB31843"},{"link_name":"CGAP Human Oesophagus Epithelium Dissociation - Tissue Stability","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cgap-human-oesophagus-epithelium-dissociation-tiss-eq2lydbxqlx9/v1"},{"link_name":"CGAP Freezing Human Tissue in Isopentane","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cgap-freezing-human-tissue-in-isopentane-n2bvjk1ngk5w/v1"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-HCAD-1"}],"name":"scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation","published_at":"2022-04-26T09:34:53+00:00","publisher_metadata":{"authors":[{"family":"Madissoon","given":"E."},{"family":"Wilbrey-Clark","given":"A."},{"family":"Miragaia","given":"R. J."},{"family":"Saeb-Parsy","given":"K."},{"family":"Mahbubani","given":"K. T."},{"family":"Georgakopoulos","given":"N."},{"family":"Harding","given":"P."},{"family":"Polanski","given":"K."},{"family":"Huang","given":"N."},{"family":"Nowicki-Osuch","given":"K."},{"family":"Fitzgerald","given":"R. C."},{"family":"Loudon","given":"K. W."},{"family":"Ferdinand","given":"J. R."},{"family":"Clatworthy","given":"M. R."},{"family":"Tsingene","given":"A."},{"family":"van Dongen","given":"S."},{"family":"Dabrowska","given":"M."},{"family":"Patel","given":"M."},{"family":"Stubbington","given":"M. J. T."},{"family":"Teichmann","given":"S. A."},{"family":"Stegle","given":"O."},{"family":"Meyer","given":"K. B."}],"is_preprint":false,"journal":"Genome Biol","published_at":1606780800.0,"published_day":1,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:55:04+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a238e9fa-2bdf-41df-8522-69046f99baff","collection_url":"https://cellxgene.cziscience.com/collections/a238e9fa-2bdf-41df-8522-69046f99baff","collection_version_id":"5a50b0f6-df76-4f9e-a1ec-2afca761fd98","consortia":["Gut Cell Atlas"],"contact_email":"martin.enge@gmail.com","contact_name":"Martin Enge","created_at":"2026-06-10T11:20:53+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"66d15835-5dc8-4e96-b0eb-f48971cb65e8","dataset_version_id":"08d4b9cf-3425-4413-a30f-8f97fe87b1e1","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"}]}],"description":"As organisms age, cells accumulate genetic and epigenetic errors that eventually lead to impaired organ function or catastrophic transformation such as cancer. Because aging reflects a stochastic process of increas ing disorder, cells in an organ will be individually affected in different ways, thus rendering bulk analyses of postmitotic adult cells difficult to interpret. Here, we directly measure the effects of aging in human tissue by performing single-cell transcriptome analysis of 2,544 human pancreas cells from eight donors spanning six decades of life. We find that islet endocrine cells from older donors display increased levels of transcriptional noise and potential fate drift. By determining the mutational history of individual cells, we uncover a novel mutational signature in healthy aging endocrine cells. Our results demonstrate the feasibility of using single-cell RNA sequencing (RNA-seq) data from primary cells to derive insights into genetic and transcriptional processes that operate on aging human tissue.","doi":"10.1016/j.cell.2017.09.004","is_pre_analysis":false,"links":[{"link_name":"GSE81547","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE81547"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/cddab57b-6868-4be4-806f-395ed9dd635a"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=adultPancreas"},{"link_name":"","link_type":"OTHER","link_url":"https://cirm.ucsc.edu/cgi-bin/cdwGetFile/quakeAdultAgingPancreas1/summary/index.html"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-81547"}],"name":"Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns","published_at":"2021-05-19T21:11:31+00:00","publisher_metadata":{"authors":[{"family":"Enge","given":"Martin"},{"family":"Arda","given":"H. 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Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain","doi":"10.1126/science.adf5357","is_pre_analysis":false,"links":[{"link_name":"GSE215353","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE215353"},{"link_name":"","link_type":"OTHER","link_url":"https://assets.nemoarchive.org/dat-jx4eu3g"}],"name":"Single-Cell DNA Methylation and 3D Genome Human Brain Atlas","published_at":"2023-10-13T18:36:13+00:00","publisher_metadata":{"authors":[{"family":"Tian","given":"Wei"},{"family":"Zhou","given":"Jingtian"},{"family":"Bartlett","given":"Anna"},{"family":"Zeng","given":"Qiurui"},{"family":"Liu","given":"Hanqing"},{"family":"Castanon","given":"Rosa G."},{"family":"Kenworthy","given":"Mia"},{"family":"Altshul","given":"Jordan"},{"family":"Valadon","given":"Cynthia"},{"family":"Aldridge","given":"Andrew"},{"family":"Nery","given":"Joseph R."},{"family":"Chen","given":"Huaming"},{"family":"Xu","given":"Jiaying"},{"family":"Johnson","given":"Nicholas D."},{"family":"Lucero","given":"Jacinta"},{"family":"Osteen","given":"Julia K."},{"family":"Emerson","given":"Nora"},{"family":"Rink","given":"Jon"},{"family":"Lee","given":"Jasper"},{"family":"Li","given":"Yang E."},{"family":"Siletti","given":"Kimberly"},{"family":"Liem","given":"Michelle"},{"family":"Claffey","given":"Naomi"},{"family":"O\u2019Connor","given":"Carolyn"},{"family":"Yanny","given":"Anna Marie"},{"family":"Nyhus","given":"Julie"},{"family":"Dee","given":"Nick"},{"family":"Casper","given":"Tamara"},{"family":"Shapovalova","given":"Nadiya"},{"family":"Hirschstein","given":"Daniel"},{"family":"Ding","given":"Song-Lin"},{"family":"Hodge","given":"Rebecca"},{"family":"Levi","given":"Boaz P."},{"family":"Keene","given":"C. Dirk"},{"family":"Linnarsson","given":"Sten"},{"family":"Lein","given":"Ed"},{"family":"Ren","given":"Bing"},{"family":"Behrens","given":"M. Margarita"},{"family":"Ecker","given":"Joseph R."}],"is_preprint":false,"journal":"Science","published_at":1697155200.0,"published_day":13,"published_month":10,"published_year":2023},"revised_at":"2026-06-11T16:55:10+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ec329aed-22bc-4d6e-8935-8282dcb1acac","collection_url":"https://cellxgene.cziscience.com/collections/ec329aed-22bc-4d6e-8935-8282dcb1acac","collection_version_id":"82093261-6226-4a3a-bb4f-d3cdfe834b5a","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. Teichmann","created_at":"2026-06-10T16:27:23+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"fcadb222-82e2-43eb-a3ab-6af0a22051fe","dataset_version_id":"f6d1e9f0-1e62-4743-9edb-9e57a6c43453","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' transcription profiling","ontology_term_id":"EFO:0030004"}],"dataset_id":"8dc858b0-b076-4326-94bb-7c2d1cd721a3","dataset_version_id":"2ebaaba9-0401-46a8-a242-f44f333ddb0d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"organoid"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 5' transcription profiling","ontology_term_id":"EFO:0030004"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"350237e0-9f48-4cbd-9140-3b44495549f3","dataset_version_id":"016717d5-115e-407d-88ad-e24b307cd025","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"Studies of human lung development have focused on epithelial and mesenchymal cell types and function, but much less is known about the developing lung immune cells, even though the airways are a major site of mucosal immunity after birth. An unanswered question is whether tissue-resident immune cells play a role in shaping the tissue as it develops in utero. Here, we profiled human embryonic and fetal lung immune cells using scRNA-seq, smFISH, and immunohistochemistry. At the embryonic stage, we observed an early wave of innate immune cells, including innate lymphoid cells, natural killer cells, myeloid cells, and lineage progenitors. By the canalicular stage, we detected naive T lymphocytes expressing high levels of cytotoxicity genes and the presence of mature B lymphocytes, including B-1 cells. Our analysis suggests that fetal lungs provide a niche for full B cell maturation. Given the presence and diversity of immune cells during development, we also investigated their possible effect on epithelial maturation. We found that IL-1\u03b2 drives epithelial progenitor exit from self-renewal and differentiation to basal cells in vitro. In vivo, IL-1\u03b2\u2013producing myeloid cells were found throughout the lung and adjacent to epithelial tips, suggesting that immune cells may direct human lung epithelial development.","doi":"10.1126/sciimmunol.adf9988","is_pre_analysis":false,"links":[{"link_name":"Fetal Lung Immune","link_type":"DATA_SOURCE","link_url":"https://fetal-lung-immune.cellgeni.sanger.ac.uk"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11528"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Peng-He-Lab/lung-immune-cell-atlas"}],"name":"Early human lung immune cell development and its role in epithelial cell fate","published_at":"2024-07-24T17:30:44+00:00","publisher_metadata":{"authors":[{"family":"Barnes","given":"Josephine L."},{"family":"Yoshida","given":"Masahiro"},{"family":"He","given":"Peng"},{"family":"Worlock","given":"Kaylee B."},{"family":"Lindeboom","given":"Rik G.H."},{"family":"Suo","given":"Chenqu"},{"family":"Pett","given":"J. Patrick"},{"family":"Wilbrey-Clark","given":"Anna"},{"family":"Dann","given":"Emma"},{"family":"Mamanova","given":"Lira"},{"family":"Richardson","given":"Laura"},{"family":"Polanski","given":"Krzysztof"},{"family":"Pennycuick","given":"Adam"},{"family":"Allen-Hyttinen","given":"Jessica"},{"family":"Herczeg","given":"Iv\u00e1n T."},{"family":"Arzili","given":"Romina"},{"family":"Hynds","given":"Robert E."},{"family":"Teixeira","given":"Vitor H."},{"family":"Haniffa","given":"Muzlifah"},{"family":"Lim","given":"Kyungtae"},{"family":"Sun","given":"Dawei"},{"family":"Rawlins","given":"Emma L."},{"family":"Oliver","given":"Amanda J."},{"family":"Lyons","given":"Paul A."},{"family":"Marioni","given":"John C."},{"family":"Ruhrberg","given":"Christiana"},{"family":"Tuong","given":"Zewen Kelvin"},{"family":"Clatworthy","given":"Menna R."},{"family":"Reading","given":"James L."},{"family":"Janes","given":"Sam M."},{"family":"Teichmann","given":"Sarah A."},{"family":"Meyer","given":"Kerstin B."},{"family":"Nikoli\u0107","given":"Marko Z."}],"is_preprint":false,"journal":"Sci. Immunol.","published_at":1703203200.0,"published_day":22,"published_month":12,"published_year":2023},"revised_at":"2026-06-11T16:55:10+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"33f48a52-31d8-4cc8-bd00-1e89c659a87f","collection_url":"https://cellxgene.cziscience.com/collections/33f48a52-31d8-4cc8-bd00-1e89c659a87f","collection_version_id":"5550adbd-a810-406b-835b-b7098d3c8245","consortia":[],"contact_email":"jacques.serizay@pasteur.fr","contact_name":"Jacques Serizay","created_at":"2026-06-10T16:29:34+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"fa49ae21-e7fc-42b6-ade3-a4c1bb6ad574","dataset_version_id":"842e359d-b36e-4cc5-bcc4-494249a5b2de","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"multiciliated ependymal cell","ontology_term_id":"CL:4052001","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f9803f15-2de5-4c9a-b3f3-1dd020f0c1e3","dataset_version_id":"b5cbb87b-0d8e-4ec9-8804-0f4a0af26ba2","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"multiciliated ependymal cell","ontology_term_id":"CL:4052001","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"72f84bfa-1d57-42bf-bea7-8472babb7ea0","dataset_version_id":"6950ad6d-b78a-446b-919a-fb77a0f9f45e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"multiciliated ependymal cell","ontology_term_id":"CL:4052001","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"612491cb-8ba7-492d-b9be-fc645ecf46a7","dataset_version_id":"6461d069-fcbb-43ea-a0e0-c46f5f1cd0c7","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"multiciliated ependymal cell","ontology_term_id":"CL:4052001","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"04e67014-9221-419a-b71e-12a5ea0ffff4","dataset_version_id":"f513cf26-370d-484a-aeb3-75d8d4405302","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"multiciliated ependymal cell","ontology_term_id":"CL:4052001","tissue_type":"primary cell culture"}]}],"description":"Meiotic division, endoreplication, and asynthetic fissions are variations of the canonical cell cycle where either replication or mitotic divisions are muted. Here, we show that multiciliated cell (MCC) differentiation, a post-mitotic process with no DNA replication or mitosis, is a new cell cycle variant. Using single-cell RNA-seq profiling, we discovered that MCC progenitors amplifying cilia-nucleating centrioles co-opt more than 70% of cell cycle factors. They share all the features of the transcriptional regulation recently described in cycling cells, including transcriptome organization along a circular trajectory. This variant is also characterized by typical waves of cyclins where non-canonical cyclins O and A1, associated with the expression of genes involved in centriole amplification and motile ciliation, replace cyclins E2 and A2 involved in DNA synthesis and mitosis onset. In addition, the primary APC/C inhibitor EMI1 is silenced. These same switches are also detected when we analyze male meiosis, another variant in which centrioles are produced independently from DNA, and grow motile cilia-like structures. Re-expressing Cyclin E2, A2, and/or EMI1 can induce partial replication and/or complete mitosis. This shows that a cell can retain the optimized principles of cell cycle gene regulation, co-opt the gene set, and regulate only certain elements to qualitatively and quantitatively divert CDK activity towards differentiation rather than division. We propose this new cell cycle variant to exploit the existence of a cytoplasmic \u2013or centriolar\u2013 CDK threshold, lower than the S-phase threshold.","doi":"10.1016/j.celrep.2024.115103","is_pre_analysis":false,"links":[{"link_name":"Damaa et al. (2025) Cell Reports","link_type":"OTHER","link_url":"https://doi.org/10.1016/j.celrep.2024.115117"},{"link_name":"GSE201773","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201773"},{"link_name":"zenodo.org","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.14105247"}],"name":"Cyclin replacement h\u0133acks the cell cycle's genetic regulatory program to orchestrate multiciliogenesis","published_at":"2025-02-03T23:49:41+00:00","publisher_metadata":{"authors":[{"family":"Serizay","given":"Jacques"},{"family":"Khoury Damaa","given":"Michella"},{"family":"Boudjema","given":"Am\u00e9lie-Rose"},{"family":"Balagu\u00e9","given":"R\u00e9mi"},{"family":"Faucourt","given":"Marion"},{"family":"Delgehyr","given":"Nathalie"},{"family":"Zaragosi","given":"Laure-Emmanuelle"},{"family":"Barbry","given":"Pascal"},{"family":"Spassky","given":"Nathalie"},{"family":"Koszul","given":"Romain"},{"family":"Meunier","given":"Alice"}],"is_preprint":false,"journal":"Cell Reports","published_at":1735689600.0,"published_day":1,"published_month":1,"published_year":2025},"revised_at":"2026-06-11T16:55:13+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ab6823e0-506e-461b-b1f9-d30e69a01687","collection_url":"https://cellxgene.cziscience.com/collections/ab6823e0-506e-461b-b1f9-d30e69a01687","collection_version_id":"da7c005b-f3c8-4370-9836-a8c6d4a0ff68","consortia":["CZI Cell Science"],"contact_email":"hammou@med.umich.edu","contact_name":"Saher Sue 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organ whose lining grows, remodels, and regenerates every menstrual cycle or upon tissue damage. Here, we applied single-cell RNA sequencing to profile more the 50,000 uterine cells from both the endometrium and myometrium of five healthy premenopausal individuals, and jointly analyzed the data with a previously published dataset from 15 subjects. The resulting normal uterus cell atlas contains more than 167K cells, representing the lymphatic endothelium, blood endothelium, stromal, ciliated epithelium, unciliated epithelium, and immune cell populations. Focused analyses within each major cell type and comparisons with subtype labels from prior studies allowed us to document supporting evidence, resolve naming conflicts, and propose a consensus annotation system of 39 subtypes. We release their gene expression centroids, differentially expressed genes, and messenger Ribonucleic Acid (mRNA) patterns of literature-based markers as a shared community resource. We identify multiple potential progenitor cells: compartment-wide progenitors for each major cell type and potential cross-lineage multipotent stromal progenitors that may replenish the epithelial, stromal, and endothelial compartments. Furthermore, many cell types and subtypes exhibit shifts in cell number and transcriptomes across different phases of the menstrual cycle. Finally, comparisons between premenopausal, postpartum, and postmenopausal samples revealed substantial alterations in tissue composition, particularly in the proportions of stromal, endothelial, and immune cells. The cell taxonomy and molecular markers we report here are expected to inform studies of both basic biology of uterine function and its disorders.","doi":"10.1073/pnas.2404775121","is_pre_analysis":false,"links":[{"link_name":"GSE260658","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE260658"},{"link_name":"E-MTAB-10287","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10287"},{"link_name":"GSE111976","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111976"}],"name":"Cellular heterogeneity and dynamics of the human uterus in healthy premenopausal women","published_at":"2025-09-26T23:00:53+00:00","publisher_metadata":{"authors":[{"family":"Ulrich","given":"Nicole D."},{"family":"Vargo","given":"Alex"},{"family":"Ma","given":"Qianyi"},{"family":"Shen","given":"Yu-chi"},{"family":"Bazzano","given":"Dominic"},{"family":"Hannum","given":"D. 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While single-cell RNA sequencing (scRNA-seq) has been widely used, interest in single-nucleus RNA sequencing (snRNA-seq) is growing due to its benefits, including the ability to analyze archival tissues and capture rare cell types that are challenging to dissociate. However, comparative studies across tissues have yielded mixed results, with some reporting enhanced cell type retention using snRNA-seq while others finding cell type identification to be challenging in snRNA-seq data. The GUDMAP consortium aims to construct a molecular atlas of the lower urinary tract (LUT); thus, we set out to determine the strengths and limitations of each approach in characterizing LUT cell types. Using the human bladder, we determined that scRNA-seq offered more discriminative gene sets for identification while snRNA-seq could facilitate capture of previously underrepresented cell types.","doi":"10.1016/j.isci.2024.111628","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://github.com/basanto/Human_Bladder_scRNA-seq_vs_snRNA-seq"},{"link_name":"GSE267964","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267964"}],"name":"Exploring the Utility of snRNA-seq in Profiling Human Bladder Tissue: A Comprehensive Comparison with scRNA-seq","published_at":"2024-11-19T21:01:01+00:00","publisher_metadata":{"authors":[{"family":"Santo","given":"Briana"},{"family":"Fink","given":"Emily E."},{"family":"Krylova","given":"Alexandra E."},{"family":"Lin","given":"Yi-Chia"},{"family":"Eltemamy","given":"Mohamed"},{"family":"Wee","given":"Alvin"},{"family":"Wessely","given":"Oliver"},{"family":"Lee","given":"Byron 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Despite rapid advances over recent years, many of the molecular and cellular processes that underlie the progressive loss of healthy physiology are poorly understood. To gain a better insight into these processes, here we generate a single-cell transcriptomic atlas across the lifespan of Mus musculus that includes data from 23 tissues and organs. We found cell-specific changes occurring across multiple cell types and organs, as well as age-related changes in the cellular composition of different organs. Using single-cell transcriptomic data, we assessed cell-type-specific manifestations of different hallmarks of ageing\u2014such as senescence, genomic instability and changes in the immune system. This transcriptomic atlas\u2014which we denote Tabula Muris Senis, or \u2018Mouse Ageing Cell Atlas\u2019\u2014provides molecular information about how the most important hallmarks of ageing are reflected in a broad range of tissues and cell types.","doi":"10.1038/s41586-020-2496-1","is_pre_analysis":false,"links":[{"link_name":"GSE132042","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132042"},{"link_name":"Processed files","link_type":"OTHER","link_url":"https://figshare.com/articles/dataset/Processed_files_to_use_with_scanpy_/8273102/2"},{"link_name":"Tabula Muris Senis","link_type":"OTHER","link_url":"https://tabula-muris-senis.ds.czbiohub.org/"},{"link_name":"SmartSeq2 for HTP Generation of FACS Sorted Single Cell Libraries V.1","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/smartseq2-for-htp-generation-of-facs-sorted-single-2uwgexe"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/czbiohub/tabula-muris-senis"}],"name":"Tabula Muris Senis","published_at":"2021-03-08T23:14:05+00:00","publisher_metadata":{"authors":[{"name":"The Tabula Muris Consortium"},{"family":"Almanzar","given":"Nicole"},{"family":"Antony","given":"Jane"},{"family":"Baghel","given":"Ankit S."},{"family":"Bakerman","given":"Isaac"},{"family":"Bansal","given":"Ishita"},{"family":"Barres","given":"Ben A."},{"family":"Beachy","given":"Philip A."},{"family":"Berdnik","given":"Daniela"},{"family":"Bilen","given":"Biter"},{"family":"Brownfield","given":"Douglas"},{"family":"Cain","given":"Corey"},{"family":"Chan","given":"Charles K. 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While the molecular basis for this heterogeneity remains uncharacterized, single-cell technologies allow us to explore the transcriptional states within tissues at an unprecedented resolution which could further understanding of these complex diseases. Here, we apply single-cell RNA-sequencing to human inflamed intestine and show that the largest differences among patients are present within the myeloid compartment including macrophages and neutrophils. Using spatial transcriptomics in human tissue at single-cell resolution (CosMx Spatial Molecular Imaging) we spatially localize each of the macrophage and neutrophil subsets identified by single-cell RNA-sequencing and unravel further macrophage diversity based on their tissue localization. Finally, single-cell RNA-sequencing combined with single-cell spatial analysis reveals a strong communication network involving macrophages and inflammatory fibroblasts. 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We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable \u201cdeveloped\u201d state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.","doi":"10.1016/j.cell.2020.08.013","is_pre_analysis":false,"links":[{"link_name":"EGA","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001004561"},{"link_name":"Mendeley","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.17632/sm67hr5bpm.1"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/1dddae6e-3753-48af-b20e-fa22abad125d"}],"name":"Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution","published_at":"2022-06-20T09:32:20+00:00","publisher_metadata":{"authors":[{"family":"Cowan","given":"Cameron S."},{"family":"Renner","given":"Magdalena"},{"family":"De Gennaro","given":"Martina"},{"family":"Gross-Scherf","given":"Brigitte"},{"family":"Goldblum","given":"David"},{"family":"Hou","given":"Yanyan"},{"family":"Munz","given":"Martin"},{"family":"Rodrigues","given":"Tiago M."},{"family":"Krol","given":"Jacek"},{"family":"Szikra","given":"Tamas"},{"family":"Cuttat","given":"Rachel"},{"family":"Waldt","given":"Annick"},{"family":"Papasaikas","given":"Panagiotis"},{"family":"Diggelmann","given":"Roland"},{"family":"Patino-Alvarez","given":"Claudia P."},{"family":"Galliker","given":"Patricia"},{"family":"Spirig","given":"Stefan E."},{"family":"Pavlinic","given":"Dinko"},{"family":"Gerber-Hollbach","given":"Nadine"},{"family":"Schuierer","given":"Sven"},{"family":"Srdanovic","given":"Aldin"},{"family":"Balogh","given":"Marton"},{"family":"Panero","given":"Riccardo"},{"family":"Kusnyerik","given":"Akos"},{"family":"Szabo","given":"Arnold"},{"family":"Stadler","given":"Michael B."},{"family":"Org\u00fcl","given":"Selim"},{"family":"Picelli","given":"Simone"},{"family":"Hasler","given":"Pascal W."},{"family":"Hierlemann","given":"Andreas"},{"family":"Scholl","given":"Hendrik P.N."},{"family":"Roma","given":"Guglielmo"},{"family":"Nigsch","given":"Florian"},{"family":"Roska","given":"Botond"}],"is_preprint":false,"journal":"Cell","published_at":1598918400.0,"published_day":1,"published_month":9,"published_year":2020},"revised_at":"2026-06-11T16:55:18+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"77446b76-1c2d-4a71-8e59-0efd4374d98e","collection_url":"https://cellxgene.cziscience.com/collections/77446b76-1c2d-4a71-8e59-0efd4374d98e","collection_version_id":"43dff8be-f8a2-4668-acdb-7e631c96e274","consortia":["CZI Cell Science"],"contact_email":"hnakshat@iu.edu","contact_name":"Harikrishna Nakshatri","created_at":"2026-06-10T17:35:03+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"61af564d-e5ea-4d34-a0f3-2668a00db376","dataset_version_id":"31798b24-255e-4726-8805-66507589ccb8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"},{"label":"upper outer quadrant of breast","ontology_term_id":"UBERON:0035328","tissue_type":"tissue"}]}],"description":"Single-nucleus analysis allows robust cell-type classification and helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Using samples from 92 women of several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells and macrophages. In addition to the known cell identity genes FOXA1 (luminal hormone sensing), EHF and ELF5 (LASP), TP63 and KRT14 (basal-myoepithelial), epithelial subtypes displayed several uncharacterized markers and inferred gene regulatory networks. By integrating breast epithelial cell gene expression signatures with spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.","doi":"10.1038/s41591-024-03011-9","is_pre_analysis":false,"links":[{"link_name":"GEO:GSE244594","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE244594"},{"link_name":"HCA portal","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/815c5ef5-0fb1-4eb7-9882-1d160362468e"}],"name":"Single-nucleus chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry","published_at":"2024-08-19T18:05:24+00:00","publisher_metadata":{"authors":[{"family":"Bhat-Nakshatri","given":"Poornima"},{"family":"Gao","given":"Hongyu"},{"family":"Khatpe","given":"Aditi S."},{"family":"Adebayo","given":"Adedeji K."},{"family":"McGuire","given":"Patrick C."},{"family":"Erdogan","given":"Cihat"},{"family":"Chen","given":"Duojiao"},{"family":"Jiang","given":"Guanglong"},{"family":"New","given":"Felicia"},{"family":"German","given":"Rana"},{"family":"Emmert","given":"Lydia"},{"family":"Sandusky","given":"George"},{"family":"Storniolo","given":"Anna Maria"},{"family":"Liu","given":"Yunlong"},{"family":"Nakshatri","given":"Harikrishna"}],"is_preprint":false,"journal":"Nat Med","published_at":1733011200.0,"published_day":1,"published_month":12,"published_year":2024},"revised_at":"2026-06-11T16:55:18+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d2684035-a36e-458e-96af-8e37930bfdf6","collection_url":"https://cellxgene.cziscience.com/collections/d2684035-a36e-458e-96af-8e37930bfdf6","collection_version_id":"1cfae73a-6e89-4b90-acdd-da8cedfef60f","consortia":["CZI Cell Science"],"contact_email":"sarah.snelling@ndorms.ox.ac.uk","contact_name":"Sarah Snelling","created_at":"2026-06-10T12:36:59+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"06ef6b36-6c9b-4e10-8a94-d0baf274276e","dataset_version_id":"9fbe9e66-2649-4bc7-b729-f89e37423552","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"tendon of semitendinosus","ontology_term_id":"UBERON:8480009","tissue_type":"tissue"}]}],"description":"The molecular and cellular basis of health in human tendons remains poorly understood. Among human tendons, hamstring tendon has markedly low pathology and can provide a prototypic healthy tendon reference. The aim of this study was to determine the transcriptomes and location of all cell types in healthy hamstring tendon. Using single nucleus RNA sequencing, we profiled the transcriptomes of 10\u2009533 nuclei from four healthy donors and identified 12 distinct cell types. We confirmed the presence of two fibroblast cell types, endothelial cells, mural cells, and immune cells, and identified cell types previously unreported in tendons, including different skeletal muscle cell types, satellite cells, adipocytes, and undefined nervous system cells. The location of these cell types within tendon was defined using spatial transcriptomics and imaging, and potential transcriptional networks and cell\u2013cell interactions were analyzed. We demonstrate that fibroblasts have the highest number of potential cell\u2013cell interactions in our dataset, are present throughout the tendon, and play an important role in the production and organization of extracellular matrix, thus confirming their role as key regulators of hamstring tendon homeostasis. Overall, our findings underscore the complexity of the cellular networks that underpin healthy human tendon function and the central role of fibroblasts as key regulators of hamstring tendon tissue homeostasis.","doi":"10.1096/fj.202300601RRR","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Botnar-MSK-Atlas/hamstring_atlas"},{"link_name":"Human Cell Atlas","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/838d4660-3d62-4b08-b32d-dc5cbd93919d"}],"name":"Single nucleus and spatial transcriptomic profiling of human healthy hamstring tendon","published_at":"2024-05-16T22:34:54+00:00","publisher_metadata":{"authors":[{"family":"Mimpen","given":"Jolet Y."},{"family":"Ramos\u2010Mucci","given":"Lorenzo"},{"family":"Paul","given":"Claudia"},{"family":"Kurjan","given":"Alina"},{"family":"Hulley","given":"Philippa A."},{"family":"Ikwuanusi","given":"Chinemerem T."},{"family":"Cohen","given":"Carla J."},{"family":"Gwilym","given":"Stephen E."},{"family":"Baldwin","given":"Mathew J."},{"family":"Cribbs","given":"Adam P."},{"family":"Snelling","given":"Sarah J. B."}],"is_preprint":false,"journal":"The FASEB Journal","published_at":1717113600.0,"published_day":31,"published_month":5,"published_year":2024},"revised_at":"2026-06-11T16:55:19+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"126afc71-47fb-4e9d-8aaf-9d9f61e0ac77","collection_url":"https://cellxgene.cziscience.com/collections/126afc71-47fb-4e9d-8aaf-9d9f61e0ac77","collection_version_id":"922b56d1-050d-4846-a63d-ae4956a99ba9","consortia":[],"contact_email":"wadriaensen@itg.be","contact_name":"Wim Adriaensen","created_at":"2026-06-10T16:38:51+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"5b25a46f-f1cf-4caa-9e10-6ab81dfe9174","dataset_version_id":"7fae5837-9482-42ea-89ba-8ab069e1b698","disease":[{"label":"HIV infectious disease || visceral leishmaniasis","ontology_term_id":"MONDO:0005109 || MONDO:0005445"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"3241c34f-581a-4de3-81fe-28e3de182680","dataset_version_id":"829fdf60-add0-4ca3-9b2f-dd86b3083885","disease":[{"label":"HIV infectious disease","ontology_term_id":"MONDO:0005109"},{"label":"HIV infectious disease || leishmaniasis","ontology_term_id":"MONDO:0005109 || MONDO:0011989"},{"label":"HIV infectious disease || visceral leishmaniasis","ontology_term_id":"MONDO:0005109 || MONDO:0005445"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"A large proportion of HIV-coinfected visceral leishmaniasis (VL) patients exhibit a chronic disease course\nwith frequent recurrence of VL, despite successful viral suppression and initial parasitological cure. Due\nto a hard-to-reach population, knowledge on immunological determinants underlying this chronic disease\ncourse is scarce, limiting treatment and patient management options. Thus, we studied alterations in\ncellular immunity with flow cytometry and single-cell RNA and T cell receptor sequencing on circulatory\nimmune cells of a longitudinal HIV cohort in North-West Ethiopia, including asymptomatically\nLeishmania-infected and active VL-HIV patients. We observed that VL chronicity in VL-HIV patients was\nassociated with persistent CD8+ T cell exhaustion and marked CD4+ T cell anergy, characterised by a high\nexpression of PD-1 and TIGIT, and a lack of lymphoproliferative response upon stimulation. These\nfindings provide a strong rationale for adjunctive immunotherapy for the treatment of chronic VL-HIV\npatients and highlight the importance of VL relapse markers.","doi":"10.1038/s42003-024-06225-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/10887674"},{"link_name":"PRJNA1093393","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1093393"}],"name":"Persistent T cell unresponsiveness associated with chronic visceral leishmaniasis in HIV-coinfected patients","published_at":"2024-06-18T15:54:08+00:00","publisher_metadata":{"authors":[{"family":"de Vrij","given":"Nicky"},{"family":"Pollmann","given":"Julia"},{"family":"Rezende","given":"Antonio M."},{"family":"Ibarra-Meneses","given":"Ana V."},{"family":"Pham","given":"Thao-Thy"},{"family":"Hailemichael","given":"Wasihun"},{"family":"Kassa","given":"Mekibib"},{"family":"Bogale","given":"Tadfe"},{"family":"Melkamu","given":"Roma"},{"family":"Yeshanew","given":"Arega"},{"family":"Mohammed","given":"Rezika"},{"family":"Diro","given":"Ermias"},{"family":"Maes","given":"Ilse"},{"family":"Domagalska","given":"Malgorzata A."},{"family":"Landuyt","given":"Hanne"},{"family":"Vogt","given":"Florian"},{"family":"van Henten","given":"Saskia"},{"family":"Laukens","given":"Kris"},{"family":"Cuypers","given":"Bart"},{"family":"Meysman","given":"Pieter"},{"family":"Beyene","given":"Hailemariam"},{"family":"Sisay","given":"Kasaye"},{"family":"Kibret","given":"Aderajew"},{"family":"Mersha","given":"Dagnew"},{"family":"Ritmeijer","given":"Koert"},{"family":"van Griensven","given":"Johan"},{"family":"Adriaensen","given":"Wim"}],"is_preprint":false,"journal":"Commun Biol","published_at":1714694400.0,"published_day":3,"published_month":5,"published_year":2024},"revised_at":"2026-06-11T16:55:20+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5900dda8-2dc3-4770-b604-084eac1c2c82","collection_url":"https://cellxgene.cziscience.com/collections/5900dda8-2dc3-4770-b604-084eac1c2c82","collection_version_id":"2d725c2d-2653-434b-8fa6-9d74c401d13d","consortia":["CZI Cell Science"],"contact_email":"ruichen@bcm.edu","contact_name":"Rui Chen","created_at":"2026-06-10T17:41:32+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"963a08cb-d995-4862-9614-f9d38a7d7540","dataset_version_id":"883270e9-41e6-4c2c-b352-b15c292d2a34","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"macula lutea","ontology_term_id":"UBERON:0000053","tissue_type":"tissue"},{"label":"peripheral region of retina","ontology_term_id":"UBERON:0013682","tissue_type":"tissue"},{"label":"retina","ontology_term_id":"UBERON:0000966","tissue_type":"tissue"}]}],"description":"As the light-sensing part of the visual system, the retina is comprised of five classes of neurons, including photoreceptors, horizontal, amacrine, bipolar, and retinal ganglion cells, along with several non-neuronal cell types such as Muller glia. These major cell classes can be further classified into hundreds of distinct cell subtypes. The development of the retina is under tight temporal control where multipotent progenitor cells differentiate into specific mature cell types in a sequential, but overlapping, order. Additionally, the developmental process is under tight spatial control, with cells at the central retina developing earlier than cells at the periphery. To provide a comprehensive view of the human fetal retina at the molecular level and investigate transcriptional regulatory mechanisms controlling the differentiation process, we profiled more than 300,000 single nuclei of the human fetal retina from 12 donors spanning post conception week 10 and 23 with Multiome RNA-seq and ATAC-seq.","doi":"10.1038/s41467-024-50853-5","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/581de139-461f-4875-b408-56453a9082c7"},{"link_name":"GSE268630","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE268630"}],"name":"Single Cell Multiome Atlas of the Human Fetal Retina","published_at":"2023-11-29T18:27:40+00:00","publisher_metadata":{"authors":[{"family":"Zuo","given":"Zhen"},{"family":"Cheng","given":"Xuesen"},{"family":"Ferdous","given":"Salma"},{"family":"Shao","given":"Jianming"},{"family":"Li","given":"Jin"},{"family":"Bao","given":"Yourong"},{"family":"Li","given":"Jean"},{"family":"Lu","given":"Jiaxiong"},{"family":"Jacobo Lopez","given":"Antonio"},{"family":"Wohlschlegel","given":"Juliette"},{"family":"Prieve","given":"Aric"},{"family":"Thomas","given":"Mervyn G."},{"family":"Reh","given":"Thomas A."},{"family":"Li","given":"Yumei"},{"family":"Moshiri","given":"Ala"},{"family":"Chen","given":"Rui"}],"is_preprint":false,"journal":"Nat Commun","published_at":1723161600.0,"published_day":9,"published_month":8,"published_year":2024},"revised_at":"2026-06-11T16:55:20+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5d445965-6f1a-4b68-ba3a-b8f765155d3a","collection_url":"https://cellxgene.cziscience.com/collections/5d445965-6f1a-4b68-ba3a-b8f765155d3a","collection_version_id":"e0d307d8-0f45-4da3-bbf0-3327f98ae641","consortia":["CZ Biohub"],"contact_email":"angela.pisco@czbiohub.org","contact_name":"Angela Pisco","created_at":"2026-06-10T16:54:30+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"e04daea4-4412-45b5-989e-76a9be070a89","dataset_version_id":"c0ee0004-7bd1-4986-9b66-8a9d3593c0e6","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo 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multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones.","doi":"10.1038/s41586-020-2922-4","is_pre_analysis":false,"links":[{"link_name":"EGAS00001004344","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001004344"},{"link_name":"PRJNA632939","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA632939"},{"link_name":"Human Lung Cell Atlas","link_type":"OTHER","link_url":"https://hlca.ds.czbiohub.org/"},{"link_name":"Synapse","link_type":"OTHER","link_url":"https://www.synapse.org/#!Synapse:syn21041850/wiki/600865"},{"link_name":"HLCA 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Its stability relies on the continued expression of genes in a subset of myonuclei, called NMJ myonuclei. Here, we perform single-nuclei RNA-sequencing (snRNA-seq) on the tibialis anterior and gastrocnemius muscles from four adult mice and identify numerous undescribed NMJ-specific transcripts. To elucidate how the NMJ transcriptome is regulated, we also performed snRNA-seq on sciatic nerve transected, botulinum toxin injected and Musk knockout muscles. These data show that NMJ gene expression is not only driven by agrin-Lrp4/MuSK signaling, but is also affected by electrical activity and trophic factors other than agrin.","doi":"10.1038/s41467-025-57487-1","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://ruegglab.shinyapps.io/snatlas/"},{"link_name":"GSE267910","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267910"}],"name":"Single Nuclei Atlas of Innervated and Denervated Mouse Muscle","published_at":"2025-02-11T00:00:04+00:00","publisher_metadata":{"authors":[{"family":"Ham","given":"Alexander S."},{"family":"Lin","given":"Shuo"},{"family":"Tse","given":"Alice"},{"family":"Th\u00fcrkauf","given":"Marco"},{"family":"McGowan","given":"Timothy J."},{"family":"J\u00f6rin","given":"Lena"},{"family":"Oliveri","given":"Filippo"},{"family":"R\u00fcegg","given":"Markus A."}],"is_preprint":false,"journal":"Nat Commun","published_at":1741132800.0,"published_day":5,"published_month":3,"published_year":2025},"revised_at":"2026-06-11T16:55:22+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"6686ada5-43a8-40b6-9a05-6894503606db","collection_url":"https://cellxgene.cziscience.com/collections/6686ada5-43a8-40b6-9a05-6894503606db","collection_version_id":"6a0cbe5d-7e9e-411f-b311-367ea41a8910","consortia":["CZI Cell Science"],"contact_email":"junzli@med.umich.edu","contact_name":"Jun Li","created_at":"2026-06-10T16:41:13+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d3d4baff-d142-4f13-acc6-96a4ef6a3e95","dataset_version_id":"92c7c761-450c-4130-9288-f355769e3cc9","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a9bedd04-51cb-42ad-83fe-cd749de71f1b","dataset_version_id":"fed15dc1-33a7-447b-a841-d0ede4cba838","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"2a65bd41-4a3f-42f4-98b2-c53962811152","dataset_version_id":"84f64d2f-60f8-4b3c-a62c-799717031e94","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]}],"description":"The reproductive and endocrine functions of the ovary involve spatially defined interactions\namong specialized cell populations. Despite the ovary's importance in fertility and endocrine health, functional attributes of ovarian cells are largely uncharacterized. Here we profiled >18,000 genes in 257 regions from the ovaries of two pre-menopausal donors to examine the functional units in the ovary. We also generated single-cell RNA sequencing data for 21,198 cells from three additional donors and identified four major cell types and four immune cell subtypes. Custom selection of sampling areas revealed distinct gene activities for oocytes, theca, and granulosa cells. These data contributed panels of oocyte-, theca-, and granulosa-specific genes, thus expanding the knowledge of molecular programs driving follicle development. Serial samples around oocytes and across the cortex and medulla uncovered previously unappreciated variation of hormone and extracellular matrix remodeling activities. This combined spatial and single-cell atlas serves as a resource for future studies of rare cells and pathological states in the ovary.","doi":"10.1126/sciadv.adm7506","is_pre_analysis":false,"links":[{"link_name":"GSE260685","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE260685"}],"name":"Cellular atlas of the human ovary using morphologically guided spatial transcriptomics and single-cell sequencing","published_at":"2024-08-26T17:37:01+00:00","publisher_metadata":{"authors":[{"family":"Jones","given":"Andrea S. K."},{"family":"Hannum","given":"D. 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In this study, we used single-nucleus multiome profiling on 232 tumor and control biopsies to comprehensively characterize the various cell types and subsets found in LBCL tumors. This approach enabled us to capture the lymphoid, myeloid, and non-hematopoietic compartments, thereby defining the cellular landscape of LBCL and identifying their stereotypical patterns of co-occurrence within lymphoma microenvironment archetype profiles (LymphoMAPs).","doi":"10.1016/j.ccell.2025.06.002","is_pre_analysis":false,"links":[{"link_name":"PMID:40920660","link_type":"OTHER","link_url":"https://pubmed.ncbi.nlm.nih.gov/40920660/"},{"link_name":"EGAD50000001491","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD50000001491"}],"name":"Single cell atlas of large B-cell lymphoma","published_at":"2025-05-23T23:07:44+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Xubin"},{"family":"Singhal","given":"Kartik"},{"family":"Deng","given":"Qing"},{"family":"Chihara","given":"Dai"},{"family":"Russler-Germain","given":"David"},{"family":"Harkins","given":"R. 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We generated human cell atlases of gene expression and chromatin accessibility in fetal tissues. For gene expression, we applied three-level combinatorial indexing to >110 samples representing 15 organs, ultimately profiling ~4 million single cells. We leveraged the literature and other atlases to identify and annotate hundreds of cell types and subtypes, both within and across tissues. Our analyses focused on organ-specific specializations of broadly distributed cell types (such as blood, endothelial, and epithelial), sites of fetal erythropoiesis (which notably included the adrenal gland), and integration with mouse developmental atlases (such as conserved specification of blood cells). These data represent a rich resource for the exploration of in vivo human gene expression in diverse tissues and cell types.","doi":"10.1126/science.aba7721","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=fetal-gene-atlas"},{"link_name":"","link_type":"OTHER","link_url":"https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=1280204515_ghYsRY4Rvd6xWbNT4JaYmq8NbAb3&db=hg38&c=chr12&g=fetalGeneAtlas"},{"link_name":"sci-RNA-seq3","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/sci-rna-seq3-9yih7ue"},{"link_name":"GSE156793","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156793"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://shendure-web.gs.washington.edu/"},{"link_name":"descartes web portal","link_type":"DATA_SOURCE","link_url":"https://descartes.brotmanbaty.org/"},{"link_name":"sci-RNA-seq3 processing pipeline","link_type":"OTHER","link_url":"https://zenodo.org/record/4013713#.YYVtCEbML0o"},{"link_name":"phs002003","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002003"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/a9301beb-e9fa-42fe-b75c-84e8a460c733"}],"name":"A human cell atlas of fetal gene expression","published_at":"2021-06-03T21:48:01+00:00","publisher_metadata":{"authors":[{"family":"Cao","given":"Junyue"},{"family":"O\u2019Day","given":"Diana R."},{"family":"Pliner","given":"Hannah A."},{"family":"Kingsley","given":"Paul D."},{"family":"Deng","given":"Mei"},{"family":"Daza","given":"Riza M."},{"family":"Zager","given":"Michael A."},{"family":"Aldinger","given":"Kimberly A."},{"family":"Blecher-Gonen","given":"Ronnie"},{"family":"Zhang","given":"Fan"},{"family":"Spielmann","given":"Malte"},{"family":"Palis","given":"James"},{"family":"Doherty","given":"Dan"},{"family":"Steemers","given":"Frank J."},{"family":"Glass","given":"Ian A."},{"family":"Trapnell","given":"Cole"},{"family":"Shendure","given":"Jay"}],"is_preprint":false,"journal":"Science","published_at":1605225600.0,"published_day":13,"published_month":11,"published_year":2020},"revised_at":"2026-06-11T16:55:31+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"18778eff-8382-4388-9d54-d5a5939eb9ee","collection_url":"https://cellxgene.cziscience.com/collections/18778eff-8382-4388-9d54-d5a5939eb9ee","collection_version_id":"5cb590c2-1478-4a17-8cc8-7a4f358e0dfc","consortia":[],"contact_email":"wangl@pumc.edu.cn","contact_name":"Li Wang","created_at":"2026-06-10T14:16:08+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"07e6773a-6c01-47aa-ac14-fbc1965edf33","dataset_version_id":"3763c3e0-7467-4713-a4ac-e71e23523f34","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"left atrium auricular region","ontology_term_id":"UBERON:0006630","tissue_type":"tissue"}]}],"description":"Owing to the prevalence and high mortality rates of cardiac diseases, a more detailed characterization of the human heart is necessary; however, this has been largely impeded by the cellular diversity of cardiac tissue and limited access to samples. By optimizing the isolation procedure of primary human cardiomyocytes (CMs), and by optimizing a single-cell approach, we isolated and profiled transcriptome of CMs and non-CMs (NCMs)\u2014from 14 healthy donors.","doi":"10.1038/s41556-019-0446-7","is_pre_analysis":false,"links":[{"link_name":"GSE109816","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE109816"}],"name":"Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac 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To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd patients. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across patient tumors and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage, and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T-cell-attracting chemokines. By identifying interacting cellular programs, we thus reveal the logic underlying spatially organized immune-malignant cell networks.","doi":"10.1016/j.cell.2021.08.003","is_pre_analysis":false,"links":[{"link_name":"Broad Institute Single Cell Portal","link_type":"DATA_SOURCE","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1162/human-colon-cancer-atlas-c295#study-visualize"},{"link_name":"CRC Immune Hubs","link_type":"OTHER","link_url":"https://broad.io/crchubs"},{"link_name":"GSE178341","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178341"},{"link_name":"dbGAP","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002407"},{"link_name":"HCA","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/6f03e4ad-9305-4bfa-a5b6-929ffb1d94bd"}],"name":"Spatially organized multicellular immune hubs in human colorectal 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Recognition of self-MHCI or MHCII by the T cell antigen receptor (TCR) determines the CD8+ T cell or CD4+ T cell lineage choice, respectively, but how distinct TCR signals drive transcriptional programs of lineage commitment remains largely unknown. Here we applied CITE-seq to measure RNA and surface proteins in thymocytes from wild-type and T cell lineage-restricted mice to generate a comprehensive timeline of cell state for each T cell lineage. These analyses identified a sequential process whereby all thymocytes initiate CD4+ T cell lineage differentiation during an initial wave of TCR signaling, followed by a second TCR signaling wave that coincides with CD8+ T cell lineage specification. CITE-seq and pharmaceutical inhibition experiments implicated a TCR-calcineurin-NFAT-GATA3 axis in driving the CD4+ T cell fate. Our data provide a resource for understanding cell fate decisions and implicate multiple redundant mechanisms in guiding lineage choice.","doi":"10.1038/s41590-023-01584-0","is_pre_analysis":false,"links":[{"link_name":"GSE186078","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE186078"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/YosefLab/Thymus_CITE-seq"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://zenodo.org/records/8102050"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"http://s133.cs.berkeley.edu:9001/Results.html"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"http://s133.cs.berkeley.edu:9002/Results.html"}],"name":"Single-cell multiomic analysis of thymocyte development reveals drivers of CD4+ T cell and CD8+ T cell lineage commitment","published_at":"2024-10-30T17:46:56+00:00","publisher_metadata":{"authors":[{"family":"Steier","given":"Zo\u00eb"},{"family":"Aylard","given":"Dominik A."},{"family":"McIntyre","given":"Laura L."},{"family":"Baldwin","given":"Isabel"},{"family":"Kim","given":"Esther Jeong Yoon"},{"family":"Lutes","given":"Lydia K."},{"family":"Ergen","given":"Can"},{"family":"Huang","given":"Tse-Shun"},{"family":"Robey","given":"Ellen A."},{"family":"Yosef","given":"Nir"},{"family":"Streets","given":"Aaron"}],"is_preprint":false,"journal":"Nat Immunol","published_at":1693526400.0,"published_day":1,"published_month":9,"published_year":2023},"revised_at":"2026-06-11T16:55:36+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"7a3044e4-6b16-4693-9504-212d9a573f80","collection_url":"https://cellxgene.cziscience.com/collections/7a3044e4-6b16-4693-9504-212d9a573f80","collection_version_id":"673a4e58-e7dc-4fff-9b91-46a4b4e8e096","consortia":[],"contact_email":"lidaniel@stanford.edu","contact_name":"Daniel Li","created_at":"2026-06-10T15:31:49+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f7417545-3cfc-45af-8dde-163e761bac8b","dataset_version_id":"0fba368a-69fd-422e-b500-e3a3e2883581","disease":[{"label":"atherosclerosis","ontology_term_id":"MONDO:0005311"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"aorta","ontology_term_id":"UBERON:0000947","tissue_type":"tissue"}]},{"assay":[{"label":"10x scATAC-seq","ontology_term_id":"EFO:0030007"}],"dataset_id":"55dd82da-3c16-48e1-abfc-439460bd8c70","dataset_version_id":"554c1b6a-9405-418d-810c-388830eae769","disease":[{"label":"atherosclerosis","ontology_term_id":"MONDO:0005311"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"aorta","ontology_term_id":"UBERON:0000947","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"15cd81c0-206c-4ee6-a0c9-2b617d7ebc40","dataset_version_id":"92f93b05-aca9-4859-8044-05859c17f95c","disease":[{"label":"atherosclerosis","ontology_term_id":"MONDO:0005311"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"aorta","ontology_term_id":"UBERON:0000947","tissue_type":"tissue"}]}],"description":"Vascular smooth muscle cells contribute to heritable coronary artery disease risk and undergo complex cell state transitions to multiple disease-related phenotypes. To investigate the genetic basis of SMC cell state trajectories that underlie the SMC component of coronary artery disease causality, we developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease model. We performed unpaired scRNAseq and scATACseq with aortic root tissue from Myh11-CreERT2 (smooth muscle) tdTomato+ ApoE-/- in the context of atherosclerotic stress with tamoxifen induction via 2x oral gavage 48 hours apart followed by high fat diet across 7 timepoints (0,3,5,7,9,12,16 weeks of diet) for scRNAseq and 6 timepoints (0,5,7,9,12,16 weeks of diet) for scATACseq assays. Parallel experiments with Tcf21flox/flox on the same background for 3 additional timepoints (5,12,16 weeks of diet) were performed to understand how loss of causal coronary artery disease gene Tcf21 impacts vascular smooth muscle cell state transitions. This comprehensive multi-modal dataset is a unique resource that maps the cellular phenotypic trajectories and vessel wall pathways across time.","doi":"10.1038/s41467-026-70530-z","is_pre_analysis":false,"links":[{"link_name":"GSE321762","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE321762"}],"name":"A Multiomic Timecourse Atlas of Murine Lineage Traced Vascular Smooth Muscle in Atherosclerosis","published_at":"2026-04-03T17:47:43+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Daniel Y."},{"family":"Kundu","given":"Soumya"},{"family":"Cheng","given":"Paul"},{"family":"Gu","given":"Wenduo"},{"family":"Worssam","given":"Matthew D."},{"family":"Jackson","given":"William R."},{"family":"Zhao","given":"Quanyi"},{"family":"Nguyen","given":"Trieu"},{"family":"Yu","given":"Amelia M."},{"family":"Monteiro","given":"Jo\u00e3o P."},{"family":"Caceres","given":"Roxanne 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However, a comprehensive single-cell atlas has not been achieved for humans. Here we use single-cell mRNA sequencing to determine the cell-type composition of all major human organs and construct a scheme for the human cell landscape (HCL). We have uncovered a single-cell hierarchy for many tissues that have not been well characterized. We established a 'single-cell HCL analysis' pipeline that helps to define human cell identity. Finally, we performed a single-cell comparative analysis of landscapes from human and mouse to identify conserved genetic networks. We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, whereas diferentiated cells are more distinct. 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While advances in the acute treatment have been made, the late-stage mortality is still high, driven by an incomplete understanding of cardiac remodeling processes. Here we used single-cell gene expression, chromatin accessibility and spatial transcriptomic profiling of different physiological zones and timepoints of human myocardial infarction and human control myocardium to generate an integrative high-resolution map of cardiac remodeling. This approach allowed us to increase spatial resolution of cell-type composition and provide spatially resolved insights into the cardiac transcriptome and epigenome with identification of distinct cellular zones of injury, repair and remodeling. We here identified and validated mechanisms of fibroblast to myofibroblast differentiation that drive cardiac fibrosis. Our study provides an integrative molecular map of human myocardial infarction and represents a reference to advanced mechanistic and therapeutic studies of cardiac disease.","doi":"10.1038/s41586-022-05060-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/6578553#.YvQwPezMI1w"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/KramannLab/visium_heart"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/6580069#.YvQwROzMI1w"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/saezlab/visium_heart"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://www.kramannlab.com"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/6578047#.YvQwPezMI1w"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001006330"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/record/6578617#.YvQwQuzMI1w"},{"link_name":"","link_type":"OTHER","link_url":"https://data.humancellatlas.org/explore/projects/e9f36305-d857-44a3-93f0-df4e6007dc97"}],"name":"Spatial multi-omic map of human myocardial infarction","published_at":"2022-08-11T13:54:22+00:00","publisher_metadata":{"authors":[{"family":"Kuppe","given":"Christoph"},{"family":"Ramirez Flores","given":"Ricardo O."},{"family":"Li","given":"Zhijian"},{"family":"Hayat","given":"Sikander"},{"family":"Levinson","given":"Rebecca T."},{"family":"Liao","given":"Xian"},{"family":"Hannani","given":"Monica T."},{"family":"Tanevski","given":"Jovan"},{"family":"W\u00fcnnemann","given":"Florian"},{"family":"Nagai","given":"James S."},{"family":"Halder","given":"Maurice"},{"family":"Schumacher","given":"David"},{"family":"Menzel","given":"Sylvia"},{"family":"Sch\u00e4fer","given":"Gideon"},{"family":"Hoeft","given":"Konrad"},{"family":"Cheng","given":"Mingbo"},{"family":"Ziegler","given":"Susanne"},{"family":"Zhang","given":"Xiaoting"},{"family":"Peisker","given":"Fabian"},{"family":"Kaesler","given":"Nadine"},{"family":"Saritas","given":"Turgay"},{"family":"Xu","given":"Yaoxian"},{"family":"Kassner","given":"Astrid"},{"family":"Gummert","given":"Jan"},{"family":"Morshuis","given":"Michiel"},{"family":"Amrute","given":"Junedh"},{"family":"Veltrop","given":"Rogier J. A."},{"family":"Boor","given":"Peter"},{"family":"Klingel","given":"Karin"},{"family":"Van Laake","given":"Linda W."},{"family":"Vink","given":"Aryan"},{"family":"Hoogenboezem","given":"Remco M."},{"family":"Bindels","given":"Eric M. J."},{"family":"Schurgers","given":"Leon"},{"family":"Sattler","given":"Susanne"},{"family":"Schapiro","given":"Denis"},{"family":"Schneider","given":"Rebekka K."},{"family":"Lavine","given":"Kory"},{"family":"Milting","given":"Hendrik"},{"family":"Costa","given":"Ivan G."},{"family":"Saez-Rodriguez","given":"Julio"},{"family":"Kramann","given":"Rafael"}],"is_preprint":false,"journal":"Nature","published_at":1661385600.0,"published_day":25,"published_month":8,"published_year":2022},"revised_at":"2026-06-11T16:55:39+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"30af2f92-7d2d-440e-b81c-e66079b5728b","collection_url":"https://cellxgene.cziscience.com/collections/30af2f92-7d2d-440e-b81c-e66079b5728b","collection_version_id":"42204c5f-bbfa-4ef6-88c2-2ced4a7d10fe","consortia":["GenitoUrinary Development Molecular Anatomy Project (GUDMAP)"],"contact_email":"c.mo@wustl.edu","contact_name":"Chia-Kuei Mo","created_at":"2026-06-10T18:20:49+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"25818bf7-e2a7-41ec-8ff2-bc369c0ff4f5","dataset_version_id":"29eec938-c857-4dc0-a3c1-db864bdea6dd","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"}]}],"description":"There is a sex bias in the incidence and progression of many kidney diseases. To better understand such sexual dimorphism, we integrated data from 6 platforms, characterizing 76 kidney samples from 68 mice at 6 developmental and adult timepoints, creating a molecular atlas of the mouse kidney across the lifespan for both sexes. We show that proximal tubules have the most sex-biased differentially expressed genes emerging after 3 weeks of age and are associated with hormonal regulations. We reveal potential mechanisms involving both direct and indirect regulation by androgens and estrogens. Spatial profiling identifies distinct sex-biased spatial patterns in the cortex and outer stripe of the outer medulla. Additionally, older mice exhibit more aging-related gene alterations in loops of Henle, proximal tubules, and collecting ducts in a sex-dependent manner. Our results enhance the understanding of spatially-resolved gene expression and hormone regulation underlying kidney sexual dimorphism across the lifespan.","doi":"10.1038/s41588-025-02161-x","is_pre_analysis":false,"links":[{"link_name":"GSE252772","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE252772"},{"link_name":"GitHub","link_type":"OTHER","link_url":"https://github.com/ding-lab/normal_mouse_kidney_scripts"},{"link_name":"Visium Data Viewer","link_type":"OTHER","link_url":"https://cmowustl.shinyapps.io/shiny_st/"}],"name":"Multi-omic and spatial analysis of mouse kidneys highlights sex-specific differences in gene regulation across the lifespan","published_at":"2025-07-03T16:19:35+00:00","publisher_metadata":{"authors":[{"family":"Chen","given":"Siqi"},{"family":"Liu","given":"Ruiyang"},{"family":"Mo","given":"Chia-Kuei"},{"family":"Wendl","given":"Michael C."},{"family":"Houston","given":"Andrew"},{"family":"Lal","given":"Preet"},{"family":"Zhao","given":"Yanyan"},{"family":"Caravan","given":"Wagma"},{"family":"Shinkle","given":"Andrew T."},{"family":"Abedin-Do","given":"Atieh"},{"family":"Naser Al Deen","given":"Nataly"},{"family":"Sato","given":"Kazuhito"},{"family":"Li","given":"Xiang"},{"family":"Targino da Costa","given":"Andr\u00e9 Luiz N."},{"family":"Li","given":"Yize"},{"family":"Karpova","given":"Alla"},{"family":"Herndon","given":"John M."},{"family":"Artyomov","given":"Maxim N."},{"family":"Rubin","given":"Joshua B."},{"family":"Jain","given":"Sanjay"},{"family":"Li","given":"Xue"},{"family":"Stewart","given":"Sheila A."},{"family":"Ding","given":"Li"},{"family":"Chen","given":"Feng"}],"is_preprint":false,"journal":"Nat Genet","published_at":1746057600.0,"published_day":1,"published_month":5,"published_year":2025},"revised_at":"2026-06-11T16:55:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"af286675-7167-4816-a907-c72d41b73d37","collection_url":"https://cellxgene.cziscience.com/collections/af286675-7167-4816-a907-c72d41b73d37","collection_version_id":"311cf0b9-7516-4638-9b81-cd46b4df87ad","consortia":["GenitoUrinary Development Molecular Anatomy Project (GUDMAP)"],"contact_email":"AHTing@mdanderson.org","contact_name":"Angela Ting","created_at":"2026-06-10T18:43:47+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"54ea5aba-3413-4c6b-a925-b4f1635d6580","dataset_version_id":"23486660-38ab-4732-9acf-80954b067a9f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5467c340-864c-4810-86ef-647039c07148","dataset_version_id":"59c361b6-d832-41c2-819b-5af0c7c281ab","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3e524d45-2265-4440-b903-3c30d51a0b17","dataset_version_id":"54132d65-74d1-489a-bc1d-9c1039e3b96c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"305c1196-76b3-42d1-818f-2694d01dbd97","dataset_version_id":"fa33ffb9-1055-4f62-bbe4-849ad469fe86","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"12c3efd8-d515-42e6-b93c-4961e599d524","dataset_version_id":"a677ef35-e47a-47ef-b30a-28aeb4139d3a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"organoid"},{"label":"ureter","ontology_term_id":"UBERON:0000056","tissue_type":"tissue"}]}],"description":"Tissue engineering offers a promising treatment strategy for ureteral strictures, but its success requires an indepth understanding of the architecture, cellular heterogeneity, and signaling pathways underlying tissue regeneration. Here, we define and spatially map cell populations within the human ureter using single-cell RNA sequencing, spatial gene expression, and immunofluorescence approaches. We focus on the stromal and urothelial cell populations to enumerate the distinct cell types composing the human ureter and infer potential cell-cell communication networks underpinning the bi-directional crosstalk between these compartments. Furthermore, we analyze and experimentally validate the importance of the sonic hedgehog (SHH) signaling pathway in adult progenitor cell maintenance. The SHH-expressing basal cells support organoid generation in vitro and accurately predict the differentiation trajectory from basal progenitor cells to terminally differentiated umbrella cells. Our results highlight the essential processes involved in adult ureter tissue homeostasis and provide a blueprint for guiding ureter tissue engineering.","doi":"10.1016/j.devcel.2022.07.004","is_pre_analysis":false,"links":[{"link_name":"GSE184111","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE184111"},{"link_name":"GSE184112","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE184112"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=adult-ureter"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://zenodo.org/records/6762182"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/2019surbhi/tinglab_ureter_analysis"}],"name":"Single-cell and spatial mapping Identify cell types and signaling Networks in the human ureter","published_at":"2024-09-24T16:23:52+00:00","publisher_metadata":{"authors":[{"family":"Fink","given":"Emily E."},{"family":"Sona","given":"Surbhi"},{"family":"Tran","given":"Uyen"},{"family":"Desprez","given":"Pierre-Emmanuel"},{"family":"Bradley","given":"Matthew"},{"family":"Qiu","given":"Hong"},{"family":"Eltemamy","given":"Mohamed"},{"family":"Wee","given":"Alvin"},{"family":"Wolkov","given":"Madison"},{"family":"Nicolas","given":"Marlo"},{"family":"Min","given":"Booki"},{"family":"Haber","given":"Georges-Pascal"},{"family":"Wessely","given":"Oliver"},{"family":"Lee","given":"Byron H."},{"family":"Ting","given":"Angela H."}],"is_preprint":false,"journal":"Developmental Cell","published_at":1659312000.0,"published_day":1,"published_month":8,"published_year":2022},"revised_at":"2026-06-11T16:55:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"cdfb9ead-cb58-4a53-879d-5e4ed5329e73","collection_url":"https://cellxgene.cziscience.com/collections/cdfb9ead-cb58-4a53-879d-5e4ed5329e73","collection_version_id":"30f5a627-5708-4723-bfce-590afcda465f","consortia":[],"contact_email":"shatteler@gmail.com","contact_name":"Justin Langerman","created_at":"2026-06-10T03:11:32+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"077b0429-0f47-48e0-879a-39eaae531d42","dataset_version_id":"6dfd8768-0acb-418d-9eb2-ebef48646a64","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"respiratory basal cell","ontology_term_id":"CL:0002633","tissue_type":"primary cell culture"}]}],"description":"Current smoking is associated with increased risk of severe COVID-19, but it is not clear how cigarette smoke (CS) exposure affects SARS-CoV-2 airway cell infection. We directly exposed air-liquid interface (ALI) cultures derived from primary human nonsmoker airway basal stem cells (ABSCs) to short term CS and then infected them with SARS-CoV-2. We found an increase in the number of infected airway cells after CS exposure with a lack of ABSC proliferation. Single-cell profiling of the cultures showed that the normal interferon response was reduced after CS exposure with infection. Treatment of CS-exposed ALI cultures with interferon \u03b2-1 abrogated the viral infection, suggesting one potential mechanism for more severe viral infection. Our data show that acute CS exposure allows for more severe airway epithelial disease from SARS-CoV-2 by reducing the innate immune response and ABSC proliferation and has implications for disease spread and severity in people exposed to CS.","doi":"10.1016/j.stem.2020.11.010","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://data.mendeley.com/datasets/jj7vb9jzk9/1"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/2a64db43-1b55-4639-aabb-8dba0145689d"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161089"},{"link_name":"","link_type":"OTHER","link_url":"https://cirm.ucsc.edu/cgi-bin/cdwGetFile/gompertsLungOrganoids/summary/index.html"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-smoking"}],"name":"Direct Exposure to SARS-CoV-2 and Cigarette Smoke Increases Infection Severity and Alters the Stem Cell-Derived Airway Repair Response","published_at":"2021-04-02T22:57:05+00:00","publisher_metadata":{"authors":[{"family":"Purkayastha","given":"Arunima"},{"family":"Sen","given":"Chandani"},{"family":"Garcia","given":"Gustavo"},{"family":"Langerman","given":"Justin"},{"family":"Shia","given":"David W."},{"family":"Meneses","given":"Luisa K."},{"family":"Vijayaraj","given":"Preethi"},{"family":"Durra","given":"Abdo"},{"family":"Koloff","given":"Caroline R."},{"family":"Freund","given":"Delilah R."},{"family":"Chi","given":"Justin"},{"family":"Rickabaugh","given":"Tammy M."},{"family":"Mulay","given":"Apoorva"},{"family":"Konda","given":"Bindu"},{"family":"Sim","given":"Myung S."},{"family":"Stripp","given":"Barry R."},{"family":"Plath","given":"Kathrin"},{"family":"Arumugaswami","given":"Vaithilingaraja"},{"family":"Gomperts","given":"Brigitte N."}],"is_preprint":false,"journal":"Cell Stem Cell","published_at":1606780800.0,"published_day":1,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:54:27+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"433700dc-e8a5-48b0-b5cd-beb22f3f88fe","collection_url":"https://cellxgene.cziscience.com/collections/433700dc-e8a5-48b0-b5cd-beb22f3f88fe","collection_version_id":"d178cb3e-ec94-446b-b20b-75397c801cb2","consortia":[],"contact_email":"andrew.yang@gladstone.ucsf.edu","contact_name":"Andrew Yang","created_at":"2026-06-10T20:16:45+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"203025fe-fa99-4d57-81da-458ed8f0c334","dataset_version_id":"25da7ccb-04ca-49d2-b00b-a794ef8c766d","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"cognitive disorder","ontology_term_id":"MONDO:0002039"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dorsolateral prefrontal cortex","ontology_term_id":"UBERON:0009834","tissue_type":"tissue"}]}],"description":"Cerebrovascular dysfunction is implicated in diverse neurological disorders, but how genetic variation in brain vascular, perivascular, and immune cell types may contribute to disease risk remains poorly understood. This gap arises in part because, while genome-wide association studies (GWASs) have identified numerous non-coding variants linked to neurological diseases, their cell type-specific effects and target genes in the human brain vasculature remain largely unknown. To address this, we developed a multi-omic vessel isolation and nuclei extraction for sequencing (MultiVINE-seq) approach to profile the paired transcriptomes and epigenomes of human brain vascular cells across 30 individuals with varying cognitive statuses. By integrating single-nucleus transcriptomic and epigenomic data, we identified key transcriptional regulators and gene networks that define human brain vascular cell specialization. Mapping GWAS variants onto our multi-omic atlas revealed that many disease risk variants lie within putative regulatory regions in vascular, perivascular, and immune cell types. Capturing these previously unaccounted-for cell types allowed us to newly map 2,605 disease-associated variants to their target cell types and genes. Cerebrovascular disease risk variants converged on vascular endothelial, mural, and perivascular fibroblast cells, disrupting extracellular matrix (ECM) gene regulation. In contrast, Alzheimer's disease (AD) risk variants were overrepresented in endothelial cells, microglia, and perivascular immune cells, perturbing the expression of adaptor proteins that fine-tune pathology-induced inflammatory responses. Notably, we uncovered a genome-wide significant AD variant predicted to enhance the expression of the T cell receptor adaptor gene PTK2B in brain CD8 T cells, potentially amplifying their infiltration, effector functions, and cytotoxicity. This finding provides genetic evidence supporting the role of adaptive immunity in AD pathogenesis. Variant-to-function relationships were validated through the integration of orthogonal epigenomic (in-silico ChIP-Seq models, Activity-By-Contact modeling), transcriptomic (eQTL), and protein-level (immunohistochemistry) data. Our work expands our view of gene regulatory networks and risk variants to include those active in the human brain vasculature, highlighting their contributions to diverse neurological disorders.","doi":null,"is_pre_analysis":false,"links":[],"name":"Brain vascular single-cell multi-omics elucidates disease risk associations","published_at":"2025-07-30T22:03:03+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:55:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"03f821b4-87be-4ff4-b65a-b5fc00061da7","collection_url":"https://cellxgene.cziscience.com/collections/03f821b4-87be-4ff4-b65a-b5fc00061da7","collection_version_id":"bbff26b1-85b6-4dbc-a949-e71dbca0c732","consortia":["CZI Cell Science","European Union\u2019s Horizon 2020"],"contact_email":"km16@sanger.ac.uk","contact_name":"Kerstin B. Meyer","created_at":"2026-06-10T03:03:33+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"edc8d3fe-153c-4e3d-8be0-2108d30f8d70","dataset_version_id":"f9efb73e-f116-46b5-a775-d4233e758024","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bronchus","ontology_term_id":"UBERON:0002185","tissue_type":"tissue"},{"label":"nasal cavity","ontology_term_id":"UBERON:0001707","tissue_type":"tissue"},{"label":"trachea","ontology_term_id":"UBERON:0003126","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"2a498ace-872a-4935-984b-1afa70fd9886","dataset_version_id":"4554d5bf-9182-47af-8caf-6b2c93513829","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"post-COVID-19 disorder","ontology_term_id":"MONDO:0100320"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"It is not fully understood why COVID-19 is typically milder in children. Here, to examine the differences between children and adults in their response to SARS-CoV-2 infection, we analysed paediatric and adult patients with COVID-19 as well as healthy control individuals (total n\u2009=\u200993) using single-cell multi-omic profiling of matched nasal, tracheal, bronchial and blood samples. In the airways of healthy paediatric individuals, we observed cells that were already in an interferon-activated state, which after SARS-CoV-2 infection was further induced especially in airway immune cells. We postulate that higher paediatric innate interferon responses restrict viral replication and disease progression. The systemic response in children was characterized by increases in naive lymphocytes and a depletion of natural killer cells, whereas, in adults, cytotoxic T cells and interferon-stimulated subpopulations were significantly increased. We provide evidence that dendritic cells initiate interferon signalling in early infection, and identify epithelial cell states associated with COVID-19 and age. Our matching nasal and blood data show a strong interferon response in the airways with the induction of systemic interferon-stimulated populations, which were substantially reduced in paediatric patients. Together, we provide several mechanisms that explain the milder clinical syndrome observed in children.","doi":"10.1038/s41586-021-04345-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/1538d572-bcb7-426b-8d2c-84f3a7f87bb0"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Teichlab/COVID-19paed"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=covid19-infection-response"},{"link_name":"EGAD00001007718","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001007718"},{"link_name":"","link_type":"OTHER","link_url":"https://www.covid19cellatlas.org/"},{"link_name":"GSE168215","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168215"},{"link_name":"cell dissociation","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cell-dissociation-from-nasal-bronchial-and-trachea-bp2l6brd5gqe/v1"}],"name":"Local and systemic responses to SARS-CoV-2 infection in children and adults","published_at":"2022-03-25T14:57:11+00:00","publisher_metadata":{"authors":[{"family":"Yoshida","given":"Masahiro"},{"family":"Worlock","given":"Kaylee B."},{"family":"Huang","given":"Ni"},{"family":"Lindeboom","given":"Rik G. 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Patrick"},{"family":"Weller","given":"Juliane"},{"family":"Prigmore","given":"Elena"},{"family":"Yung","given":"Henry"},{"family":"Mehta","given":"Puja"},{"family":"Saleh","given":"Aarash"},{"family":"Saigal","given":"Anita"},{"family":"Chu","given":"Vivian"},{"family":"Cohen","given":"Jonathan M."},{"family":"Cane","given":"Clare"},{"family":"Iordanidou","given":"Aikaterini"},{"family":"Shibuya","given":"Soichi"},{"family":"Reuschl","given":"Ann-Kathrin"},{"family":"Herczeg","given":"Iv\u00e1n T."},{"family":"Argento","given":"A. Christine"},{"family":"Wunderink","given":"Richard G."},{"family":"Smith","given":"Sean B."},{"family":"Poor","given":"Taylor A."},{"family":"Gao","given":"Catherine A."},{"family":"Dematte","given":"Jane E."},{"family":"Budinger","given":"G. R. Scott"},{"family":"Donnelly","given":"Helen K."},{"family":"Markov","given":"Nikolay S."},{"family":"Lu","given":"Ziyan"},{"family":"Reynolds","given":"Gary"},{"family":"Haniffa","given":"Muzlifah"},{"family":"Bowyer","given":"Georgina S."},{"family":"Coates","given":"Matthew"},{"family":"Clatworthy","given":"Menna R."},{"family":"Calero-Nieto","given":"Fernando J."},{"family":"G\u00f6ttgens","given":"Berthold"},{"family":"O\u2019Callaghan","given":"Christopher"},{"family":"Sebire","given":"Neil J."},{"family":"Jolly","given":"Clare"},{"family":"De Coppi","given":"Paolo"},{"family":"Smith","given":"Claire M."},{"family":"Misharin","given":"Alexander V."},{"family":"Janes","given":"Sam M."},{"family":"Teichmann","given":"Sarah A."},{"family":"Nikoli\u0107","given":"Marko Z."},{"family":"Meyer","given":"Kerstin B."},{"name":"NU SCRIPT Study Investigators"}],"is_preprint":false,"journal":"Nature","published_at":1644451200.0,"published_day":10,"published_month":2,"published_year":2022},"revised_at":"2026-06-11T16:54:27+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0f528c8a-a25c-4840-8fa3-d156fa11086f","collection_url":"https://cellxgene.cziscience.com/collections/0f528c8a-a25c-4840-8fa3-d156fa11086f","collection_version_id":"7cf0a24a-d5c4-4968-8dcb-1e0beafb64cf","consortia":["CZI Cell Science","Human BioMolecular Atlas Program (HuBMAP)","Kidney Precision Medicine Project (KPMP)"],"contact_email":"info@kpmp.org","contact_name":"KPMP","created_at":"2026-06-10T07:41:15+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"dea717d4-7bc0-4e46-950f-fd7e1cc8df7d","dataset_version_id":"08648660-9898-4644-a9a1-ff3a159a0041","disease":[{"label":"acute kidney injury","ontology_term_id":"MONDO:0002492"},{"label":"chronic kidney disease","ontology_term_id":"MONDO:0005300"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a12ccb9b-4fbe-457d-8590-ac78053259ef","dataset_version_id":"02d5db96-d67e-45f2-b556-b6bd99753665","disease":[{"label":"acute kidney injury","ontology_term_id":"MONDO:0002492"},{"label":"chronic kidney disease","ontology_term_id":"MONDO:0005300"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"renal medulla","ontology_term_id":"UBERON:0000362","tissue_type":"tissue"},{"label":"renal papilla","ontology_term_id":"UBERON:0001228","tissue_type":"tissue"}]}],"description":"Understanding kidney health and disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We have applied single-cell and single-nucleus assays to a broad spectrum of healthy reference and disease kidneys. This has provided a high-resolution cellular atlas that includes rare and novel cell populations. We further identify and define cellular states altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states affecting several nephron segments. These analyses further define biological pathways relevant to injury niches, including signatures underlying the transition from reference to predicted maladaptive states that are associated with a decline in kidney function during chronic kidney disease. Our collaborative efforts across the Kidney Precision Medicine Project (KPMP), the Human BioMolecular Atlas Program (HuBMAP) and the Human Cell Atlas consortia aim to generate a comprehensive human kidney cell atlas that includes injury and disease-relevant cell states and neighborhoods as a valuable resource to the research community. Here we provide an expanded data set from that published previously (Lake et al., Nature 2023) that includes additional KPMP biopsy data.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"KPMP","link_type":"DATA_SOURCE","link_url":"https://atlas.kpmp.org/repository/"},{"link_name":"Atlas Version 1.0","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/bcb61471-2a44-4d00-a0af-ff085512674c"},{"link_name":"Altas Version 2.0","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/9c9d04c4-8899-417f-bb6f-6107dcadf14f"}],"name":"An atlas of healthy and injured cell states and niches in the human kidney (Version 1.5)","published_at":"2024-05-13T18:29:57+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:54:27+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a261413d-835b-4f1e-ab0c-dada55ea6afd","collection_url":"https://cellxgene.cziscience.com/collections/a261413d-835b-4f1e-ab0c-dada55ea6afd","collection_version_id":"4cc1a56c-5983-4536-87ce-839411839628","consortia":[],"contact_email":"alex.bondoc@cchmc.org","contact_name":"Alexander Bondoc","created_at":"2026-06-10T20:34:08+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ec6ceff8-c8bc-488d-b6bf-30df2fa92169","dataset_version_id":"d66d154b-5ff6-4b1a-b25e-376cf4784bb7","disease":[{"label":"blastoma","ontology_term_id":"MONDO:0005565"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"}]}],"description":"Hepatoblastoma (HB) is the most common primary liver malignancy of childhood, and molecular investigations are limited and effective treatment options for chemoresistant disease are lacking. There is a knowledge gap in the investigation of key driver cells of HB in tumor. Here we show single cell ribonucleic acid sequencing (scRNAseq) analysis of human tumor, background liver, and patient derived xenograft (PDX) to demonstrate gene expression patterns within tumor and to identify intratumor cell subtype heterogeneity to define differing roles in pathogenesis based on intracellular signaling in pediatric HB. We have identified a driver tumor cell cluster in HB by genetic expression which can be examined to define disease mechanism and treatments. Identification of both critical mechanistic pathways combined with unique cell populations provide the basis for discovery and investigation of novel treatment strategies in vitro and in vivo.","doi":"10.1038/s42003-021-02562-8","is_pre_analysis":false,"links":[{"link_name":"GSE180665","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE180665"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/2084526b-a66f-4c40-bb89-6fd162f2eb38"},{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/KANG-BIOINFO/scRNA-seq_Hepatoblastoma"}],"name":"Identification of distinct tumor cell populations and key genetic mechanisms through single cell sequencing in hepatoblastoma","published_at":"2022-06-30T13:10:24+00:00","publisher_metadata":{"authors":[{"family":"Bondoc","given":"Alexander"},{"family":"Glaser","given":"Kathryn"},{"family":"Jin","given":"Kang"},{"family":"Lake","given":"Charissa"},{"family":"Cairo","given":"Stefano"},{"family":"Geller","given":"James"},{"family":"Tiao","given":"Gregory"},{"family":"Aronow","given":"Bruce"}],"is_preprint":false,"journal":"Commun Biol","published_at":1638316800.0,"published_day":1,"published_month":12,"published_year":2021},"revised_at":"2026-06-11T16:55:43+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"380ade76-e561-49a8-afb2-0f10b39c2c72","collection_url":"https://cellxgene.cziscience.com/collections/380ade76-e561-49a8-afb2-0f10b39c2c72","collection_version_id":"1db666f3-1c32-495f-bc2b-bffc100a3afd","consortia":["CZI Cell Science"],"contact_email":"mengjiechen@uchicago.edu","contact_name":"Mengjie Chen","created_at":"2026-06-10T20:51:11+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"0436a180-cb44-47ba-8ffa-807b7a468469","dataset_version_id":"fb14bb6c-8b8d-4fc7-8983-4b8d9bce9afa","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ampulla of fallopian tube","ontology_term_id":"UBERON:0012648","tissue_type":"tissue"},{"label":"fimbria of fallopian tube","ontology_term_id":"UBERON:8410010","tissue_type":"tissue"}]}],"description":"The fallopian tube undergoes extensive molecular changes during the menstrual cycle and menopause. We use single-cell RNA and ATAC sequencing to construct a comprehensive cell atlas of healthy human fallopian tubes during the menstrual cycle and menopause. Our scRNA-seq comparison of 85,107 pre- and 46,111 post-menopausal fallopian tube cells reveals substantial shifts in cell type frequencies, gene expression, transcription factor activity, and cell-to-cell communications during menopause and menstrual cycle. Menstrual cycle dependent hormonal changes regulate distinct molecular states in fallopian tube secretory epithelial cells. Postmenopausal fallopian tubes show high chromatin accessibility in transcription factors associated with aging such as Jun, Fos, and BACH1/2, while hormone receptors were generally downregulated, a small proportion of secretory epithelial cells had high expression of ESR2, IGF1R, and LEPR. While a pre-menopausal secretory epithelial gene cluster is enriched in the immunoreactive molecular subtype, a subset of genes expressed in post-menopausal secretory epithelial cells show enrichment in the mesenchymal molecular type of high-grade serous ovarian cancer.","doi":"10.1038/s41467-024-55440-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001006780"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS50000000628"}],"name":"A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause","published_at":"2024-09-03T20:38:49+00:00","publisher_metadata":{"authors":[{"family":"Weigert","given":"Melanie"},{"family":"Li","given":"Yan"},{"family":"Zhu","given":"Lisha"},{"family":"Eckart","given":"Heather"},{"family":"Bajwa","given":"Preety"},{"family":"Krishnan","given":"Rahul"},{"family":"Ackroyd","given":"Sarah"},{"family":"Lastra","given":"Ricardo"},{"family":"Bilecz","given":"Agnes"},{"family":"Basu","given":"Anindita"},{"family":"Lengyel","given":"Ernst"},{"family":"Chen","given":"Mengjie"}],"is_preprint":false,"journal":"Nat 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]}],"description":"A balanced bone marrow hematopoietic reference map to allow for efficient and precise cell type classification in single-cell datasets.","doi":"10.1158/2643-3230.BCD-24-0342","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/andygxzeng/BoneMarrowMap"}],"name":"A Balanced Bone Marrow Reference Map of Hematopoietic Development","published_at":"2024-06-26T15:10:40+00:00","publisher_metadata":{"authors":[{"family":"Zeng","given":"Andy G.X."},{"family":"Iacobucci","given":"Ilaria"},{"family":"Shah","given":"Sayyam"},{"family":"Mitchell","given":"Amanda"},{"family":"Wong","given":"Gordon"},{"family":"Bansal","given":"Suraj"},{"family":"Chen","given":"David"},{"family":"Gao","given":"Qingsong"},{"family":"Kim","given":"Hyerin"},{"family":"Kennedy","given":"James A."},{"family":"Arruda","given":"Andrea"},{"family":"Minden","given":"Mark D."},{"family":"Haferlach","given":"Torsten"},{"family":"Mullighan","given":"Charles G."},{"family":"Dick","given":"John E."}],"is_preprint":false,"journal":"Blood Cancer 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v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"589fe605-6d49-4abe-bff8-1675511c689a","dataset_version_id":"5b0e8244-cc05-47ab-819f-87747854c04c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dorsal lateral plate region","ontology_term_id":"UBERON:0003105","tissue_type":"tissue"},{"label":"embryo","ontology_term_id":"UBERON:0000922","tissue_type":"tissue"},{"label":"embryoid body","ontology_term_id":"UBERON:0014374","tissue_type":"organoid"}]}],"description":"Single-cell combinatorial indexing RNA-seq (sci-RNA-seq) of human iPSC-derived embryoid bodies spanning day 7 through day 21 of hematopoietic differention. 10X 3\u2019 sc-RNA-seq of human iPSC-derived embryoid bodies from day 8 of differentiation integrated with 10X 3\u2019 sc-RNA-seq published human embryo datasets encompassing HSC-independent , Carnegie Stage (CS) 10-13 (Zeng et al. 2019), and HSC-dependent, CS 14-17 (Crosse et al. 2020, Calvanese et al. 2022), timepoints. There are 3 visualizations: (1) sci-RNA-seq Days 7-21 iPSC-derived Embryoid Bodies during Hematopoietic Differentiation, (2) 10X Day 8 iPSC-derived Embryoid Body during Hematopoietic Differentiation data alone, and (3) 10X Day 8 iPSC-derived Embryoid Body during Hematopoietic Differentiation integrated with human embryo 10X data from Zeng et al. 2019, Crosse et al. 2020, and Calvanese et al. 2022.","doi":"10.1016/j.stemcr.2025.102641","is_pre_analysis":false,"links":[{"link_name":"GSE274082","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274082"},{"link_name":"GSE274084","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274084"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/FredHutch/Wellington-et-al-2024"}],"name":"Developmental Regulation of Endothelial-to-Hematopoietic Transition from iPSCs","published_at":"2025-02-03T20:31:31+00:00","publisher_metadata":{"authors":[{"family":"Wellington","given":"Rachel"},{"family":"Cheng","given":"Xiaoyi"},{"family":"Dutta","given":"Shuvra"},{"family":"Campbell","given":"Clyde A."},{"family":"Trapnell","given":"Cole"},{"family":"Espin-Palazon","given":"Raquel"},{"family":"Hadland","given":"Brandon"},{"family":"Doulatov","given":"Sergei"}],"is_preprint":false,"journal":"Stem Cell Reports","published_at":1759276800.0,"published_day":1,"published_month":10,"published_year":2025},"revised_at":"2026-06-11T16:54:28+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2a79d190-a41e-4408-88c8-ac5c4d03c0fc","collection_url":"https://cellxgene.cziscience.com/collections/2a79d190-a41e-4408-88c8-ac5c4d03c0fc","collection_version_id":"60cefa15-3c55-4b4b-886d-7322621ab2d4","consortia":[],"contact_email":"neal.ravindra@yale.edu","contact_name":"Neal G. 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Moreover, by performing integrative analyses of our single-nuclei multi-omics data with common genetic variants associated with age at natural menopause (ANM) from genome-wide association studies, we demonstrate a global impact of functional variants on changes in gene regulatory networks across ovarian cell types. Finally, we nominate functional non-coding regulatory variants, their target genes and ovarian cell types and regulatory mechanisms that underlie genetic association with ANM. 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T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their T-cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell maturation and behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we develop Slide-TCR-seq, a 10-\u00b5m-resolution method to sequence whole transcriptomes and TCRs within intact tissues. We confirm the ability of Slide-TCR-seq to map the characteristic architecture of T cells and their receptors in mouse spleen. In human lymph nodes and tonsil, we identified spatially distinct TCR repertoires. Spatial profiling of T cell clonotypes and their infiltration in renal cell carcinoma and melanoma specimens identified inter- and intra-clonotype transcriptional heterogeneity. Our method facilitates the dissection of the immune microenvironment, yielding insights into the complex spatial relationships between T cell clonotypes, neighboring cell types, and gene expression that drive T cell responses across diseases.","doi":"10.1016/j.immuni.2022.09.002","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1348/slide-tcr-seq-data"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/soph-liu/Slide-TCR-seq"}],"name":"Spatially mapping T cell receptors and transcriptomes","published_at":"2023-09-29T19:16:15+00:00","publisher_metadata":{"authors":[{"family":"Liu","given":"Sophia"},{"family":"Iorgulescu","given":"J. Bryan"},{"family":"Li","given":"Shuqiang"},{"family":"Borji","given":"Mehdi"},{"family":"Barrera-Lopez","given":"Irving A."},{"family":"Shanmugam","given":"Vignesh"},{"family":"Lyu","given":"Haoxiang"},{"family":"Morriss","given":"Julia W."},{"family":"Garcia","given":"Zoe N."},{"family":"Murray","given":"Evan"},{"family":"Reardon","given":"David A."},{"family":"Yoon","given":"Charles H."},{"family":"Braun","given":"David A."},{"family":"Livak","given":"Kenneth J."},{"family":"Wu","given":"Catherine J."},{"family":"Chen","given":"Fei"}],"is_preprint":false,"journal":"Immunity","published_at":1664582400.0,"published_day":1,"published_month":10,"published_year":2022},"revised_at":"2026-06-11T16:54:37+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"99f1515b-46a2-4bc4-94c3-f62659dc1eb4","collection_url":"https://cellxgene.cziscience.com/collections/99f1515b-46a2-4bc4-94c3-f62659dc1eb4","collection_version_id":"7ce0bdab-c328-44cb-a786-18dd4a9b22a4","consortia":[],"contact_email":"joan_brugge@hms.harvard.edu","contact_name":"Joan Brugge","created_at":"2026-06-10T02:03:02+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"9a64bf99-ebe5-4276-93a8-bee9dff1cd47","dataset_version_id":"af5464b2-fd5c-45e1-aae9-daddfd9f3aea","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"}]}],"description":"Single cell RNA sequencing was performed on 52,681 cells from 16 breast tissues, including tissues from noncarriers (n = 3) and carriers of germline mutations in BRCA1 (n = 6), BRCA2 (n = 6), or RAD51C (n = 1), spanning a range of ages (25\u201365) and parities. Gene expression signatures were generated for cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation.","doi":"10.1016/j.devcel.2022.05.003","is_pre_analysis":false,"links":[{"link_name":"GSE180878","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE180878"},{"link_name":"SCP1731","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1731/a-human-breast-atlas-integrating-single-cell-proteomics-and-transcriptomics"},{"link_name":"Synapse","link_type":"OTHER","link_url":"https://www.synapse.org/#!Synapse:syn26560310"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/9b876d31-0739-4e96-9846-f76e6a427279"}],"name":"A human breast atlas integrating single-cell proteomics and transcriptomics","published_at":"2023-08-10T20:10:07+00:00","publisher_metadata":{"authors":[{"family":"Gray","given":"G. 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T. 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To address this gap, we generated a high-resolution multimodal cell atlas of the developing adolescent brain using paired single-nucleus RNA and ATAC sequencing (snRNA-seq + snATAC-seq) from cortex, hippocampus, and amygdala tissue of six donors aged 6-15 years, profiling 88,658 high-quality nuclei. Integrative analyses identified 36 enhancer-driven gene regulatory networks (eGRNs) with significant age-dependent dynamics in the transition from childhood to adolescence. The majority of adolescence-associated eGRNs were active in oligodendrocytes and their precursors, reflecting active oligodendrogenesis and myelin remodeling during this developmental period. Notably, age-associated cis-regulatory elements were enriched for expression quantitative trait loci (eQTLs) and colocalized with genetic variants linked to both neurodevelopmental and neurodegenerative disorders, suggesting that regulatory networks may be shared across normal adolescent brain development and disease vulnerability. This multimodal cell atlas provides a valuable resource for understanding the human adolescent brain and offers new insights into the molecular origins of neuropsychiatric disorders.\n\nFragments data for donor G133 are included with previously published Collection:  https://cellxgene.cziscience.com/collections/9e4e8f1d-d905-4d4f-b343-84889d0f9ffe","doi":"10.64898/2026.02.20.707029","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/984ce0a2-682d-47a3-b80e-1354dfe51ca3"}],"name":"A multimodal single-cell atlas of the adolescent brain reveals gene regulatory networks linking development to disease risk","published_at":"2026-02-24T23:20:15+00:00","publisher_metadata":{"authors":[{"family":"Galv\u00e3o","given":"Isabella C."},{"family":"Lemoine","given":"Manuela"},{"family":"Waichman","given":"Tom\u00e1s V."},{"family":"Chandarana","given":"Bhavyaa"},{"family":"H\u00e9bert","given":"Steven"},{"family":"de Oliveira","given":"Thais C."},{"family":"dos Santos","given":"Luciano H. 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the full cellular diversity of specific organs. However, these studies rarely examine organ-specific immune cells. Stewart et al. sequenced healthy adult and fetal kidney samples at a single-cell level to define the heterogeneity in epithelial, myeloid, and lymphoid cells. From this dataset, they identified zonation of cells, with relevance to disease and the varied perturbations that occur in different tumor settings. This profiling of the human kidney generates a comprehensive census of existing cell populations that will help inform the diagnosis and treatment of kidney-related diseases.","doi":"10.1126/science.aat5031","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://www.kidneycellatlas.org/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/abe1a013-af7a-45ed-8c26-f3793c24a1f4"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=kidney-atlas"},{"link_name":"","link_type":"OTHER","link_url":"https://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg38&g=kidneyStewart&position=default"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-HCAD-10"}],"name":"Spatiotemporal immune zonation of the human kidney","published_at":"2022-06-14T23:41:20+00:00","publisher_metadata":{"authors":[{"family":"Stewart","given":"Benjamin J."},{"family":"Ferdinand","given":"John R."},{"family":"Young","given":"Matthew D."},{"family":"Mitchell","given":"Thomas J."},{"family":"Loudon","given":"Kevin W."},{"family":"Riding","given":"Alexandra M."},{"family":"Richoz","given":"Nathan"},{"family":"Frazer","given":"Gordon L."},{"family":"Staniforth","given":"Joy U. 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Here we present a multi-omics spatial lung atlas to define novel cell types which we map back into the macro- and micro-anatomical tissue context to define functional tissue microenvironments. Firstly, we have generated single cell and nuclei RNA sequencing, VDJ-sequencing and Visium Spatial Transcriptomics data sets from 5 different locations of the human lung and airways. Secondly, we define additional cell types/states, as well as spatially map novel and known human airway cell types, such as adult lung chondrocytes, submucosal gland (SMG) duct cells, distinct pericyte and smooth muscle subtypes, immune-recruiting fibroblasts, peribronchial and perichondrial fibroblasts, peripheral nerve associated fibroblasts and Schwann cells. Finally, we define a survival niche for IgA-secreting plasma cells at the SMG, comprising the newly defined epithelial SMG-Duct cells, and B and T lineage immune cells. Using our transcriptomic data for cell-cell interaction analysis, we propose a signalling circuit that establishes and supports this niche. Overall, we provide a transcriptional and spatial lung atlas with multiple novel cell types that allows for the study of specific tissue microenvironments such as the newly defined gland-associated lymphoid niche (GALN).","doi":"10.1038/s41588-022-01243-4","is_pre_analysis":false,"links":[{"link_name":"PRJEB52292","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB52292"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/957261f7-2bd6-4358-a6ed-24ee080d5cfc"},{"link_name":"E-MTAB-11640","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11640"},{"link_name":"S-BIAD570","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BIAD570"},{"link_name":"","link_type":"OTHER","link_url":"https://5locationslung.cellgeni.sanger.ac.uk/"}],"name":"A spatially resolved atlas of the human lung characterizes a gland-associated immune niche","published_at":"2024-02-13T22:44:13+00:00","publisher_metadata":{"authors":[{"family":"Madissoon","given":"Elo"},{"family":"Oliver","given":"Amanda J."},{"family":"Kleshchevnikov","given":"Vitalii"},{"family":"Wilbrey-Clark","given":"Anna"},{"family":"Polanski","given":"Krzysztof"},{"family":"Richoz","given":"Nathan"},{"family":"Ribeiro Orsi","given":"Ana"},{"family":"Mamanova","given":"Lira"},{"family":"Bolt","given":"Liam"},{"family":"Elmentaite","given":"Rasa"},{"family":"Pett","given":"J. Patrick"},{"family":"Huang","given":"Ni"},{"family":"Xu","given":"Chuan"},{"family":"He","given":"Peng"},{"family":"Dabrowska","given":"Monika"},{"family":"Pritchard","given":"Sophie"},{"family":"Tuck","given":"Liz"},{"family":"Prigmore","given":"Elena"},{"family":"Perera","given":"Shani"},{"family":"Knights","given":"Andrew"},{"family":"Oszlanczi","given":"Agnes"},{"family":"Hunter","given":"Adam"},{"family":"Vieira","given":"Sara F."},{"family":"Patel","given":"Minal"},{"family":"Lindeboom","given":"Rik G. 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This process is orchestrated by numerous temporally and spatially restricted gene expression programmes, making congenital alterations in phenotype common2. Decades of work with model organisms have defined the fundamental mechanisms underlying vertebrate limb development, but an in-depth characterization of this process in humans has yet to be performed. Here we detail human embryonic limb development across space and time using single-cell and spatial transcriptomics. We demonstrate extensive diversification of cells from a few multipotent progenitors to myriad differentiated cell states, including several novel cell populations. We uncover two waves of human muscle development, each characterized by different cell states regulated by separate gene expression programmes, and identify musculin (MSC) as a key transcriptional repressor maintaining muscle stem cell identity. Through assembly of multiple anatomically continuous spatial transcriptomic samples using VisiumStitcher, we map cells across a sagittal section of a whole fetal hindlimb. We reveal a clear anatomical segregation between genes linked to brachydactyly and polysyndactyly, and uncover transcriptionally and spatially distinct populations of the mesenchyme in the autopod. Finally, we perform single-cell RNA sequencing on mouse embryonic limbs to facilitate cross-species developmental comparison, finding substantial homology between the two species.","doi":"10.1038/s41586-023-06806-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://developmental.cellatlas.io/embryonic-limb"},{"link_name":"mouse scRNA-seq","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10514"},{"link_name":"human Visium","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10367"},{"link_name":"human scRNA-seq","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8813"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Peng-He-Lab/limbcellatlas"}],"name":"A human embryonic limb cell atlas resolved in space and time","published_at":"2024-06-06T17:08:17+00:00","publisher_metadata":{"authors":[{"family":"Zhang","given":"Bao"},{"family":"He","given":"Peng"},{"family":"Lawrence","given":"John E. G."},{"family":"Wang","given":"Shuaiyu"},{"family":"Tuck","given":"Elizabeth"},{"family":"Williams","given":"Brian A."},{"family":"Roberts","given":"Kenny"},{"family":"Kleshchevnikov","given":"Vitalii"},{"family":"Mamanova","given":"Lira"},{"family":"Bolt","given":"Liam"},{"family":"Polanski","given":"Krzysztof"},{"family":"Li","given":"Tong"},{"family":"Elmentaite","given":"Rasa"},{"family":"Fasouli","given":"Eirini S."},{"family":"Prete","given":"Martin"},{"family":"He","given":"Xiaoling"},{"family":"Yayon","given":"Nadav"},{"family":"Fu","given":"Yixi"},{"family":"Yang","given":"Hao"},{"family":"Liang","given":"Chen"},{"family":"Zhang","given":"Hui"},{"family":"Blain","given":"Raphael"},{"family":"Chedotal","given":"Alain"},{"family":"FitzPatrick","given":"David R."},{"family":"Firth","given":"Helen"},{"family":"Dean","given":"Andrew"},{"family":"Bayraktar","given":"Omer Ali"},{"family":"Marioni","given":"John C."},{"family":"Barker","given":"Roger A."},{"family":"Storer","given":"Mekayla A."},{"family":"Wold","given":"Barbara J."},{"family":"Zhang","given":"Hongbo"},{"family":"Teichmann","given":"Sarah A."}],"is_preprint":false,"journal":"Nature","published_at":1732147200.0,"published_day":21,"published_month":11,"published_year":2024},"revised_at":"2026-06-11T16:54:38+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bcb61471-2a44-4d00-a0af-ff085512674c","collection_url":"https://cellxgene.cziscience.com/collections/bcb61471-2a44-4d00-a0af-ff085512674c","collection_version_id":"379e9a9b-8436-496f-9370-042491bc27d6","consortia":["CZI Cell Science","Human BioMolecular Atlas Program (HuBMAP)","Kidney Precision Medicine Project (KPMP)"],"contact_email":"info@kpmp.org","contact_name":"KPMP","created_at":"2026-06-10T22:02:56+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"32b9bdce-2481-4c85-ba1b-6ad5fcea844c","dataset_version_id":"3ae68468-89f7-4941-a945-f7bae9b2cbea","disease":[{"label":"acute kidney injury","ontology_term_id":"MONDO:0002492"},{"label":"chronic kidney disease","ontology_term_id":"MONDO:0005300"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0b75c598-0893-4216-afe8-5414cab7739d","dataset_version_id":"4cd166f1-ef51-4137-869d-0a3688bc2bc8","disease":[{"label":"acute kidney injury","ontology_term_id":"MONDO:0002492"},{"label":"chronic kidney disease","ontology_term_id":"MONDO:0005300"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"renal medulla","ontology_term_id":"UBERON:0000362","tissue_type":"tissue"},{"label":"renal papilla","ontology_term_id":"UBERON:0001228","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"07854d9c-5375-4a9b-ac34-fa919d3c3686","dataset_version_id":"5dc03d39-ac5f-49e1-8630-a64d2e6e293b","disease":[{"label":"acute kidney injury","ontology_term_id":"MONDO:0002492"},{"label":"chronic kidney disease","ontology_term_id":"MONDO:0005300"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"},{"label":"renal medulla","ontology_term_id":"UBERON:0000362","tissue_type":"tissue"},{"label":"renal papilla","ontology_term_id":"UBERON:0001228","tissue_type":"tissue"}]}],"description":"Understanding kidney health and disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We have applied single-cell and single-nucleus assays to a broad spectrum of healthy reference and disease kidneys. This has provided a high-resolution cellular atlas that includes rare and novel cell populations. We further identify and define cellular states altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states affecting several nephron segments. These analyses further define biological pathways relevant to injury niches, including signatures underlying the transition from reference to predicted maladaptive states that are associated with a decline in kidney function during chronic kidney disease. Our collaborative efforts across the Kidney Precision Medicine Project (KPMP), the Human BioMolecular Atlas Program (HuBMAP) and the Human Cell Atlas consortia aim to generate a comprehensive human kidney cell atlas that includes injury and disease-relevant cell states and neighborhoods as a valuable resource to the research community.","doi":"10.1038/s41586-023-05769-3","is_pre_analysis":false,"links":[{"link_name":"KPMP","link_type":"DATA_SOURCE","link_url":"https://www.kpmp.org/"},{"link_name":"GSE169285","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169285"},{"link_name":"","link_type":"OTHER","link_url":"https://atlas.kpmp.org/explorer"},{"link_name":"Single-Nucleus RNA-Sequencing","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/10x-genomics-single-nucleus-rna-sequencing-for-tra-86khzcw"},{"link_name":"Isolation of single nuclei from solid tissues","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.ufketkw"},{"link_name":"HuBMAP","link_type":"DATA_SOURCE","link_url":"https://hubmapconsortium.org/"},{"link_name":"Single-Cell RNA-Sequencing","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/single-cell-rna-sequencing-scrna-seq-7dthi6n"},{"link_name":"Preparation of Adult Human Kidney Tissue for Single Nucleus RNA-seq and Other Multiomics Studies","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/preparation-of-adult-human-kidney-tissue-for-singl-yxmvm78xbv3p/v1"},{"link_name":"GSE183279","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE183279"},{"link_name":"Atlas Version 1.5","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/0f528c8a-a25c-4840-8fa3-d156fa11086f"},{"link_name":"Atlas Version 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Our analyses reveal the dynamic cellular states that shape human B cell\u2013mediated immunity and highlight how antibody isotype may play a role during their antibody-based selection.","doi":"10.1126/sciimmunol.abe6291","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/24d0dbbc-54eb-4904-8141-934d26f1c936"},{"link_name":"","link_type":"OTHER","link_url":"https://www.tonsilimmune.org/"},{"link_name":"E-MTAB-8999","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8999"},{"link_name":"E-MTAB-9003","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9003"},{"link_name":"E-MTAB-9005","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-9005"}],"name":"Single-cell analysis of human B cell maturation predicts how antibody class switching shapes selection dynamics","published_at":"2023-02-23T00:27:39+00:00","publisher_metadata":{"authors":[{"family":"King","given":"Hamish W."},{"family":"Orban","given":"Nara"},{"family":"Riches","given":"John C."},{"family":"Clear","given":"Andrew J."},{"family":"Warnes","given":"Gary"},{"family":"Teichmann","given":"Sarah A."},{"family":"James","given":"Louisa K."}],"is_preprint":false,"journal":"Sci. 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Raw data counts were generated with the 10X Genomics cellranger pipeline followed by velocyto UMI counting.  Souporcell SNP analysis showed that all cells except a few erythrocytes were of foetal origin. Low quality cells were removed based on UMI counts and doublet analysis and the final dataset \nwas clustered resulting in 245 clusters. Cell types were annotated at several levels of granularity.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/linnarsson-lab/human-meninges-development"}],"name":"Single cell RNA sequencing of the human embryonic meninges at 5-13 weeks post conception","published_at":"2025-07-08T19:55:25+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:55:52+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3a844375-60ea-474b-adf1-98e76928baee","collection_url":"https://cellxgene.cziscience.com/collections/3a844375-60ea-474b-adf1-98e76928baee","collection_version_id":"f7281b78-3e3a-4c89-b2e7-96155853871b","consortia":[],"contact_email":"zlatko.trajanoski@i-med.ac.at","contact_name":"Zlatko Trajanoski","created_at":"2026-06-10T07:06:51+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' 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These samples encompass the full spectrum of disease progression, from normal colon to polyps, primary tumors, and metastases, covering both early and advanced stages of colorectal cancer (CRC). Additionally, to address the limited availability of neutrophil single-cell data, we supplemented the atlas by analyzing samples from 12 CRC patients using a platform that captures cells with very low transcript counts. We present a high-resolution view of CRC with 61 major cell types or states, revealing different cell-type composition patterns in CRC subtypes. These findings could have important implications for developing improved cancer immunotherapy approaches in CRC.","doi":"10.1016/j.ccell.2025.12.003","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://crc.icbi.at/"},{"link_name":"Pre-trained reference models (scVI/scANVI)","link_type":"DATA_SOURCE","link_url":"https://zenodo.org/records/17878122"}],"name":"Single-cell integration and multi-modal profiling reveals phenotypes and spatial organization of neutrophils in colorectal cancer","published_at":"2026-06-08T19:57:10+00:00","publisher_metadata":{"authors":[{"family":"Marteau","given":"Valentin"},{"family":"Nemati","given":"Niloofar"},{"family":"Handler","given":"Kristina"},{"family":"Raju","given":"Deeksha"},{"family":"Kirchmair","given":"Alexander"},{"family":"Rieder","given":"Dietmar"},{"family":"Kvalem Soto","given":"Erika"},{"family":"Fotakis","given":"Georgios"},{"family":"De Lange","given":"Glenn"},{"family":"Carollo","given":"Sandro"},{"family":"Boeck","given":"Nina"},{"family":"Rossi","given":"Alessia"},{"family":"Daum","given":"Sophia"},{"family":"Scheiber","given":"Alexandra"},{"family":"Amann","given":"Arno"},{"family":"Seeber","given":"Andreas"},{"family":"Gasser","given":"Elisabeth"},{"family":"Ormanns","given":"Steffen"},{"family":"G\u00fcnther","given":"Michael"},{"family":"Martowicz","given":"Agnieszka"},{"family":"Loncova","given":"Zuzana"},{"family":"Lamberti","given":"Giorgia"},{"family":"Krogsdam","given":"Anne"},{"family":"Carlet","given":"Michela"},{"family":"Horvath","given":"Lena"},{"family":"Eling","given":"Marie Theres"},{"family":"Fazilaty","given":"Hassan"},{"family":"Valenta","given":"Tomas"},{"family":"Sturm","given":"Gregor"},{"family":"Sopper","given":"Sieghart"},{"family":"Pircher","given":"Andreas"},{"family":"Stoitzner","given":"Patrizia"},{"family":"Wild","given":"Peter J."},{"family":"Welker","given":"Patrick"},{"family":"May","given":"Pascal J."},{"family":"Ziegler","given":"Paul"},{"family":"Tschurtschenthaler","given":"Markus"},{"family":"Neureiter","given":"Daniel"},{"family":"Huemer","given":"Florian"},{"family":"Greil","given":"Richard"},{"family":"Weiss","given":"Lukas"},{"family":"Ijsselsteijn","given":"Marieke"},{"family":"de Miranda","given":"Noel F.C.C."},{"family":"Wolf","given":"Dominik"},{"family":"Arnold","given":"Isabelle C."},{"family":"Salcher","given":"Stefan"},{"family":"Trajanoski","given":"Zlatko"}],"is_preprint":false,"journal":"Cancer Cell","published_at":1767225600.0,"published_day":1,"published_month":1,"published_year":2026},"revised_at":"2026-06-11T16:54:36+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"071b706a-7ea7-47a4-bddf-6457725839fc","collection_url":"https://cellxgene.cziscience.com/collections/071b706a-7ea7-47a4-bddf-6457725839fc","collection_version_id":"a484fe58-d71b-4bd8-917d-b9cbf9e96914","consortia":[],"contact_email":"jessica.whittle@cruk.manchester.ac.uk","contact_name":"Jessica Whittle","created_at":"2026-06-10T08:17:50+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"},{"label":"10x transcription profiling","ontology_term_id":"EFO:0030080"},{"label":"SORT-seq","ontology_term_id":"EFO:0030074"},{"label":"Seq-Well","ontology_term_id":"EFO:0008919"},{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"4568ebb2-468c-4381-9ce7-81cd97abcd22","dataset_version_id":"538e5e8b-3400-4b23-b380-17a152949c63","disease":[{"label":"myeloid leukemia","ontology_term_id":"MONDO:0004643"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]}],"description":"Large scale integration of published scRNA-seq datasets created a unique single-cell transcriptomic atlas for AML (AML scAtlas), totalling 748,679 cells, from 159 AML patients and 51 healthy donors from 20 different studies. 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formation","ontology_term_id":"UBERON:0001885","tissue_type":"tissue"},{"label":"hippocampal field","ontology_term_id":"UBERON:0003876","tissue_type":"tissue"},{"label":"lateral septal complex","ontology_term_id":"UBERON:0007628","tissue_type":"tissue"},{"label":"nucleus accumbens","ontology_term_id":"UBERON:0001882","tissue_type":"tissue"},{"label":"olfactory cortex","ontology_term_id":"UBERON:0002894","tissue_type":"tissue"},{"label":"orbitofrontal cortex","ontology_term_id":"UBERON:0004167","tissue_type":"tissue"},{"label":"pallidum","ontology_term_id":"UBERON:0006514","tissue_type":"tissue"},{"label":"piriform cortex","ontology_term_id":"UBERON:0004725","tissue_type":"tissue"},{"label":"primary auditory cortex","ontology_term_id":"UBERON:0034751","tissue_type":"tissue"},{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"},{"label":"primary somatosensory cortex","ontology_term_id":"UBERON:0008933","tissue_type":"tissue"},{"label":"secondary somatosensory cortex","ontology_term_id":"UBERON:0008934","tissue_type":"tissue"}]}],"description":"The mammalian cerebrum performs high level sensory, motor control and cognitive functions through highly specialized cortical networks and subcortical nuclei. Recent surveys of mouse and human brains with single cell transcriptomics and high-throughput imaging technologies have uncovered hundreds of neuronal cell types and a variety of non-neuronal cell types distributed in different brain regions, but the cell-type-specific transcriptional regulatory programs responsible for the unique identity and function of each brain cell type have yet to be elucidated. Here, we probe the accessible chromatin in >800,000 individual nuclei from 45 regions spanning the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to define 491,818 candidate cis regulatory DNA elements in 160 distinct sub-types. We link a significant fraction of them to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of non-coding risk variants associated with various neurological disease and traits in humans.","doi":"10.1038/s41586-021-03604-1","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/yal054/snATACutils"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-wywv153"},{"link_name":"","link_type":"OTHER","link_url":"http://catlas.org/mousebrain/#!/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/r3fang/SnapATAC"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://renlab.sdsc.edu/renlab_website/"}],"name":"An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum","published_at":"2021-03-18T21:54:05+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Yang Eric"},{"family":"Preissl","given":"Sebastian"},{"family":"Hou","given":"Xiaomeng"},{"family":"Zhang","given":"Ziyang"},{"family":"Zhang","given":"Kai"},{"family":"Qiu","given":"Yunjiang"},{"family":"Poirion","given":"Olivier B."},{"family":"Li","given":"Bin"},{"family":"Chiou","given":"Joshua"},{"family":"Liu","given":"Hanqing"},{"family":"Pinto-Duarte","given":"Antonio"},{"family":"Kubo","given":"Naoki"},{"family":"Yang","given":"Xiaoyu"},{"family":"Fang","given":"Rongxin"},{"family":"Wang","given":"Xinxin"},{"family":"Han","given":"Jee Yun"},{"family":"Lucero","given":"Jacinta"},{"family":"Yan","given":"Yiming"},{"family":"Miller","given":"Michael"},{"family":"Kuan","given":"Samantha"},{"family":"Gorkin","given":"David"},{"family":"Gaulton","given":"Kyle J."},{"family":"Shen","given":"Yin"},{"family":"Nunn","given":"Michael"},{"family":"Mukamel","given":"Eran A."},{"family":"Behrens","given":"M. Margarita"},{"family":"Ecker","given":"Joseph R."},{"family":"Ren","given":"Bing"}],"is_preprint":false,"journal":"Nature","published_at":1633564800.0,"published_day":7,"published_month":10,"published_year":2021},"revised_at":"2026-06-11T16:54:39+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"cc431242-35ea-41e1-a100-41e0dec2665b","collection_url":"https://cellxgene.cziscience.com/collections/cc431242-35ea-41e1-a100-41e0dec2665b","collection_version_id":"9beb4e9b-e5b5-4750-b460-01cd398a3b53","consortia":["CZI Cell Science"],"contact_email":"nir.yosef@weizmann.ac.il","contact_name":"Nir Yosef","created_at":"2026-06-10T16:41:56+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' 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body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"},{"label":"spleen","ontology_term_id":"UBERON:0002106","tissue_type":"tissue"},{"label":"thoracic lymph node","ontology_term_id":"UBERON:0007644","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"11ae668a-88c2-4d86-ba08-524fe576a882","dataset_version_id":"4fd4c4f7-3501-4c00-b15d-e2ea3e1b4792","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"},{"label":"epithelial lining fluid","ontology_term_id":"UBERON:0035963","tissue_type":"tissue"},{"label":"inguinal lymph node","ontology_term_id":"UBERON:0001542","tissue_type":"tissue"},{"label":"jejunal epithelium","ontology_term_id":"UBERON:0000400","tissue_type":"tissue"},{"label":"jejunum lamina propria","ontology_term_id":"UBERON:8600034","tissue_type":"tissue"},{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"},{"label":"mesenteric lymph node","ontology_term_id":"UBERON:0002509","tissue_type":"tissue"},{"label":"spleen","ontology_term_id":"UBERON:0002106","tissue_type":"tissue"},{"label":"thoracic lymph node","ontology_term_id":"UBERON:0007644","tissue_type":"tissue"}]}],"description":"The immune system comprises multiple cell lineages and heterogeneous subsets found in blood and tissues throughout the body. While human immune responses differ between sites and over age, the underlying sources of variation remain unclear as most studies are limited to peripheral blood. Here, we took a systems approach to comprehensively profile RNA and surface protein expression of over 1.25 million immune cells isolated from blood, lymphoid organs, and mucosal tissues of 24 organ donors aged 20-75 years. We applied a multimodal classifier to annotate the major immune cell lineages (T cells, B cells, innate lymphoid cells, and myeloid cells) and their corresponding subsets across the body, leveraging probabilistic modeling to define bases for immune variations across donors, tissue, and age. We identified dominant tissue-specific effects on immune cell composition and function across lineages for lymphoid sites, intestines, and blood-rich tissues. Age-associated effects were intrinsic to both lineage and site as manifested by macrophages in mucosal sites, B cells in lymphoid organs, and T and NK cells in blood-rich sites. Our results reveal tissue-specific signatures of immune homeostasis throughout the body and across different ages. This information provides a basis for defining the transcriptional underpinnings of immune variation and potential associations with disease-associated immune pathologies across the human lifespan.","doi":"10.1038/s41590-025-02241-4","is_pre_analysis":false,"links":[{"link_name":"GSE299043","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299043"},{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/YosefLab/CZI-Immuneaging"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/6179c38c-9987-4e7c-a4bb-d34cf33a3c3f"}],"name":"Multimodal profiling reveals tissue-directed signatures of human immune cells altered with age","published_at":"2025-06-06T19:26:08+00:00","publisher_metadata":{"authors":[{"family":"Wells","given":"Steven B."},{"family":"Rainbow","given":"Daniel B."},{"family":"Mark","given":"Michal"},{"family":"Szabo","given":"Peter A."},{"family":"Ergen","given":"Can"},{"family":"Caron","given":"Daniel P."},{"family":"Maceiras","given":"Ana Raquel"},{"family":"Rahmani","given":"Elior"},{"family":"Benuck","given":"Eli"},{"family":"Valiollah Pour Amiri","given":"Valeh"},{"family":"Chen","given":"David"},{"family":"Wagner","given":"Allon"},{"family":"Howlett","given":"Sarah K."},{"family":"Jarvis","given":"Lorna B."},{"family":"Ellis","given":"Karen L."},{"family":"Kubota","given":"Masaru"},{"family":"Matsumoto","given":"Rei"},{"family":"Mahbubani","given":"Krishnaa"},{"family":"Saeb-Parsy","given":"Kouresh"},{"family":"Conde","given":"Cecilia Dominguez"},{"family":"Richardson","given":"Laura"},{"family":"Xu","given":"Chuan"},{"family":"Li","given":"Shuang"},{"family":"Mamanova","given":"Lira"},{"family":"Bolt","given":"Liam"},{"family":"Wilk","given":"Alicja"},{"family":"Teichmann","given":"Sarah A."},{"family":"Farber","given":"Donna L."},{"family":"Sims","given":"Peter A."},{"family":"Jones","given":"Joanne L."},{"family":"Yosef","given":"Nir"}],"is_preprint":false,"journal":"Nat Immunol","published_at":1756684800.0,"published_day":1,"published_month":9,"published_year":2025},"revised_at":"2026-06-11T16:52:23+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"eb735cc9-d0a7-48fa-b255-db726bf365af","collection_url":"https://cellxgene.cziscience.com/collections/eb735cc9-d0a7-48fa-b255-db726bf365af","collection_version_id":"1c99391d-bbe6-4aa5-8f4c-ef6de8f6e9e2","consortia":["CZI Cell Science"],"contact_email":"rv4@sanger.ac.uk","contact_name":"Roser Vento-Tormo","created_at":"2026-06-10T13:07:17+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"c2a461b1-0c15-4047-9fcb-1f966fe55100","dataset_version_id":"b112be5b-d8c9-455d-9a62-7b960e71a06d","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Human blood samples were obtained from a cohort of patients under SARS-CoV-2 infection with pre-existing immunological condition, including patients with autoimmune diseases such as rheumatoid arthritis (RA), psoriasis (Ps), Sjogren syndrome (Sj), eosinophilic granulomatosis with polyangiitis (EGPA) and multiple sclerosis (MS). Immunodeficient patients consisted in individuals diagnosed with common variable immunodeficiency (CVID), missing IgA and IgM isotypes and displaying missing or reduced IgG, as well as one individual with lymphopenia and another with bone marrow failure of unknown origin. In some cases, PBMCs samples before, during and after SARS-CoV-2 infection were collected from the same individual (CVID patient 1 and CVID patient 2). For some individuals, nasal swab samples were also collected in parallel with the PBMC sample. For nasal sample collection, the swab was gently inserted along the nasal septum, just above the floor of the nasal passage, to the nasopharynx, until resistance was felt and then the swab was rotated 5 times. The patients were previously diagnosed according to European Society for Immunodeficiencies (ESID) criteria and established criteria for autoimmune diseases (Perricone and Valesini, 2014). They were collected at Hospital La Paz, Hospital La Princesa, Hospital Vall d\u2019Hebron, Hospital Can Ruti and Hospital Bellvitge (Spain), and Medical Center-University of Freiburg (Germany). All donors received oral and written information about the possibility that their blood and nasal biopsies would be used for research purposes, and any questions that arose were then answered. Before giving their first sample the donors signed a consent form approved by the Ethics Committee at their corresponding hospitals, which adhered to the principles set out in the WMA Declaration of Helsinki.","doi":"10.1101/2020.11.20.20227355","is_pre_analysis":false,"links":[{"link_name":"Purification of PBMCs","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/purification-of-pbmcs-e6nvw93r2gmk/v1"},{"link_name":"","link_type":"OTHER","link_url":"https://www.covid19cellatlas.org/"},{"link_name":"CITE-seq for PBMCs","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cite-seq-for-pbmcs-8epv514qjl1b/v1"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-autoimmune-pbmc"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/2d4d89f2-ebeb-467c-ae60-a3efc5e8d4ba"}],"name":"Sampling peripheral blood and matched nasal swabs from donors with prior immunodeficiencies and autoimmune conditions infected with SARS-CoV-2","published_at":"2022-03-31T09:12:27+00:00","publisher_metadata":{"authors":[{"name":"Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia"},{"family":"Ballestar","given":"Esteban"},{"family":"Farber","given":"Donna L."},{"family":"Glover","given":"Sarah"},{"family":"Horwitz","given":"Bruce"},{"family":"Meyer","given":"Kerstin"},{"family":"Nikoli\u0107","given":"Marko"},{"family":"Ordovas-Montanes","given":"Jose"},{"family":"Sims","given":"Peter"},{"family":"Shalek","given":"Alex"},{"family":"Vandamme","given":"Niels"},{"family":"Vandekerckhove","given":"Linos"},{"family":"Vento-Tormo","given":"Roser"},{"family":"Villani","given":"Alexandra Chloe"}],"is_preprint":true,"journal":"medRxiv","published_at":1606089600.0,"published_day":23,"published_month":11,"published_year":2020},"revised_at":"2026-06-11T16:52:26+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"e8c525c0-1026-49df-be15-2d427c1a06d1","collection_url":"https://cellxgene.cziscience.com/collections/e8c525c0-1026-49df-be15-2d427c1a06d1","collection_version_id":"a1e6119e-45e4-4755-9fb3-5913e3c7b193","consortia":["Human Cell Atlas (HCA)"],"contact_email":"igor.adameyko@meduniwien.ac.at","contact_name":"Prof Igor Adameyko","created_at":"2026-06-10T13:26:22+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5eb05c46-9d59-4971-8bcb-2660f74860b9","dataset_version_id":"c36bab70-e905-4a6e-884e-1f63712880f3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"molar dental pulp","ontology_term_id":"UBERON:0015838","tissue_type":"tissue"},{"label":"tooth root apical papilla","ontology_term_id":"UBERON:8480031","tissue_type":"tissue"}]}],"description":"Understanding cell types and mechanisms of dental growth is essential for reconstruction and engineering of teeth. Therefore, we investigated cellular composition of growing and non-growing mouse and human teeth. As a result, we report an unappreciated cellular complexity of the continuously-growing mouse incisor, which suggests a coherent model of cell dynamics enabling unarrested growth. This model relies on spatially-restricted stem, progenitor and differentiated populations in the epithelial and mesenchymal compartments underlying the coordinated expansion of two major branches of pulpal cells and diverse epithelial subtypes. Further comparisons of human and mouse teeth yield both parallelisms and differences in tissue heterogeneity and highlight the specifics behind growing and non-growing modes. Despite being similar at a coarse level, mouse and human teeth reveal molecular differences and species-specific cell subtypes suggesting possible evolutionary divergence. Overall, here we provide an atlas of human and mouse teeth with a focus on growth and differentiation.","doi":"10.1038/s41467-020-18512-7","is_pre_analysis":false,"links":[{"link_name":"GSE146123","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146123"},{"link_name":"Cellxgene Gateway","link_type":"LAB_WEBSITE","link_url":"https://adameykolab.hifo.meduniwien.ac.at/cellxgene_public/view/2020_NatCom_Krivanek_Soldatov/Human_adult_and_growing_molar_teeth.h5ad/"}],"name":"Human adult and growing molar teeth","published_at":"2026-04-24T17:17:41+00:00","publisher_metadata":{"authors":[{"family":"Krivanek","given":"Jan"},{"family":"Soldatov","given":"Ruslan A."},{"family":"Kastriti","given":"Maria Eleni"},{"family":"Chontorotzea","given":"Tatiana"},{"family":"Herdina","given":"Anna Nele"},{"family":"Petersen","given":"Julian"},{"family":"Szarowska","given":"Bara"},{"family":"Landova","given":"Marie"},{"family":"Matejova","given":"Veronika Kovar"},{"family":"Holla","given":"Lydie Izakovicova"},{"family":"Kuchler","given":"Ulrike"},{"family":"Zdrilic","given":"Ivana Vidovic"},{"family":"Vijaykumar","given":"Anushree"},{"family":"Balic","given":"Anamaria"},{"family":"Marangoni","given":"Pauline"},{"family":"Klein","given":"Ophir D."},{"family":"Neves","given":"Vitor C. M."},{"family":"Yianni","given":"Val"},{"family":"Sharpe","given":"Paul T."},{"family":"Harkany","given":"Tibor"},{"family":"Metscher","given":"Brian D."},{"family":"Baj\u00e9noff","given":"Marc"},{"family":"Mina","given":"Mina"},{"family":"Fried","given":"Kaj"},{"family":"Kharchenko","given":"Peter V."},{"family":"Adameyko","given":"Igor"}],"is_preprint":false,"journal":"Nat Commun","published_at":1600819200.0,"published_day":23,"published_month":9,"published_year":2020},"revised_at":"2026-06-11T16:52:28+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"44531dd9-1388-4416-a117-af0a99de2294","collection_url":"https://cellxgene.cziscience.com/collections/44531dd9-1388-4416-a117-af0a99de2294","collection_version_id":"d900c30c-9659-4b0a-9a77-a2abca1d1bdd","consortia":["CZI Cell Science"],"contact_email":"tallulandrews@gmail.com","contact_name":"Tallulah Andrews","created_at":"2026-06-10T03:17:27+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ddb22b3d-a75c-4dd1-9730-dff7fc8ca530","dataset_version_id":"135bdd30-d055-48fc-9578-6fe3a6df3c18","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"9f049476-2431-4645-a2d6-f6e85892b603","dataset_version_id":"66e4b618-9ac0-439f-a97d-4cf12bad7ef4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3b6ed41e-10a1-47dd-b995-8cde7d041fd6","dataset_version_id":"22316ea6-bc10-4546-88ab-c5b3c420bdb5","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"0895c838-e550-48a3-a777-dbcd35d30272","dataset_version_id":"0d5aa69f-1ad1-470f-9a1b-4a167da3b545","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"caudate lobe of liver","ontology_term_id":"UBERON:0001117","tissue_type":"tissue"}]}],"description":"The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver\u2019s parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.","doi":"10.1002/hep4.1854","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/tallulandrews/Liver_sc_sn_paper_scripts"},{"link_name":"GSE185477","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185477"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/8a666b76-daaf-4b1f-9414-e4807a1d1e8b"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/human-liver-caudate-lobe-dissociation-for-scrna-se-q26g77j1gwz1/v2"},{"link_name":"","link_type":"OTHER","link_url":"https://macparlandlab.shinyapps.io/healthylivermapspatialgui/"}],"name":"Single-Cell, Single-Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity","published_at":"2022-01-07T18:27:42+00:00","publisher_metadata":{"authors":[{"family":"Andrews","given":"Tallulah S."},{"family":"Atif","given":"Jawairia"},{"family":"Liu","given":"Jeff C."},{"family":"Perciani","given":"Catia T."},{"family":"Ma","given":"Xue\u2010Zhong"},{"family":"Thoeni","given":"Cornelia"},{"family":"Slyper","given":"Michal"},{"family":"Eraslan","given":"G\u00f6kcen"},{"family":"Segerstolpe","given":"Asa"},{"family":"Manuel","given":"Justin"},{"family":"Chung","given":"Sai"},{"family":"Winter","given":"Erin"},{"family":"Cirlan","given":"Iulia"},{"family":"Khuu","given":"Nicholas"},{"family":"Fischer","given":"Sandra"},{"family":"Rozenblatt\u2010Rosen","given":"Orit"},{"family":"Regev","given":"Aviv"},{"family":"McGilvray","given":"Ian D."},{"family":"Bader","given":"Gary D."},{"family":"MacParland","given":"Sonya A."}],"is_preprint":false,"journal":"Hepatol Commun","published_at":1648771200.0,"published_day":1,"published_month":4,"published_year":2022},"revised_at":"2026-06-11T16:52:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3c4f0970-7614-43de-beb7-6128b3cb74ed","collection_url":"https://cellxgene.cziscience.com/collections/3c4f0970-7614-43de-beb7-6128b3cb74ed","collection_version_id":"6655a434-f525-414a-b4b9-6e758f09bacc","consortia":[],"contact_email":"alexmascension@gmail.com","contact_name":"Alex Mart\u00ednez Ascensi\u00f3n","created_at":"2026-06-10T22:41:41+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' 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S3","ontology_term_id":"EFO:0030019"}],"dataset_id":"a19d1667-a7b5-4556-9e5f-f9bfa690c0f1","dataset_version_id":"8ae4471a-2e70-47b5-bc42-4f0df26a9996","disease":[{"label":"injury","ontology_term_id":"MONDO:0021178"},{"label":"keloid","ontology_term_id":"MONDO:0005348"},{"label":"localized scleroderma","ontology_term_id":"MONDO:0019562"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"hindlimb skin","ontology_term_id":"UBERON:0003532","tissue_type":"tissue"},{"label":"inguinal region skin","ontology_term_id":"UBERON:8410021","tissue_type":"tissue"},{"label":"lower leg skin","ontology_term_id":"UBERON:0004264","tissue_type":"tissue"},{"label":"skin of abdomen","ontology_term_id":"UBERON:0001416","tissue_type":"tissue"},{"label":"skin of back","ontology_term_id":"UBERON:0001068","tissue_type":"tissue"},{"label":"skin of body","ontology_term_id":"UBERON:0002097","tissue_type":"tissue"},{"label":"skin of cheek","ontology_term_id":"UBERON:0008803","tissue_type":"tissue"},{"label":"skin of chest","ontology_term_id":"UBERON:0001868","tissue_type":"tissue"},{"label":"skin of face","ontology_term_id":"UBERON:1000021","tissue_type":"tissue"},{"label":"skin of forearm","ontology_term_id":"UBERON:0003403","tissue_type":"tissue"},{"label":"skin of hip","ontology_term_id":"UBERON:0001554","tissue_type":"tissue"},{"label":"skin of leg","ontology_term_id":"UBERON:0001511","tissue_type":"tissue"},{"label":"skin of pes","ontology_term_id":"UBERON:0001513","tissue_type":"tissue"},{"label":"skin of shoulder","ontology_term_id":"UBERON:0001483","tissue_type":"tissue"},{"label":"skin of trunk","ontology_term_id":"UBERON:0001085","tissue_type":"tissue"}]}],"description":"Numerous single-cell RNA sequencing (scRNAseq) studies have unveiled large transcriptomic heterogeneity within both human and mouse dermal fibroblasts, but a consensus atlas that spans both species is lacking. Here, by studying 25 human and 9 mouse datasets through a semi-supervised procedure, we categorize 15 distinct human fibroblast subpopulations across 5 main axes. Analysis of human fibroblast markers characteristic of each subpopulation suggested diverse functions, such as position-dependent ECM synthesis, association with immune responses or structural roles in skin appendages. Similarly, mouse fibroblasts were categorized into 17 subpopulations across 5 axes. Comparison of mouse and human fibroblast subpopulations highlighted similarities suggesting a degree of functional overlap, though nuanced differences were also noted: transcriptomically, human axes seem to segregate by function, while mouse axes seem to prioritize positional information over function. Importantly, addition of newer datasets did not significantly change the defined subpopulation structure. This study enhances our understanding of dermal fibroblast diversity, shedding light on species-specific distinctions as well as shared functionalities.","doi":"10.1101/2024.09.05.611379","is_pre_analysis":false,"links":[{"link_name":"zenodo (notebooks)","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.7492966"},{"link_name":"zenodo (human h5ad)","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.7785089"},{"link_name":"zenodo (mouse h5ad)","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.7785085"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/alexmascension/fibroblast-population-detection"}],"name":"Human and mouse dermal fibroblast atlas","published_at":"2024-04-18T15:48:20+00:00","publisher_metadata":{"authors":[{"family":"Ascensi\u00f3n","given":"Alex M."},{"family":"Izeta","given":"Ander"}],"is_preprint":true,"journal":"bioRxiv","published_at":1725926400.0,"published_day":10,"published_month":9,"published_year":2024},"revised_at":"2026-06-11T16:55:54+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"db468083-041c-41ca-8f6f-bf991a070adf","collection_url":"https://cellxgene.cziscience.com/collections/db468083-041c-41ca-8f6f-bf991a070adf","collection_version_id":"8908b77f-b332-41e4-8dea-cb1f8e3cf431","consortia":["CZI Cell Science"],"contact_email":"szhong@eng.ucsd.edu","contact_name":"Sheng Zhong","created_at":"2026-06-09T22:18:02+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"6cda3b13-7257-45b9-ac20-0a7e6697e4f2","dataset_version_id":"aaeb9a19-a77c-49a8-bdfa-1949773738b0","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"endothelial cell","ontology_term_id":"CL:0000115","tissue_type":"primary cell culture"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"42b6a476-c51d-4f8b-b68b-44941b3a11bf","dataset_version_id":"9199a4c8-f8e9-4cc6-8c3b-bd9b6e5524d4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"type 2 diabetes mellitus","ontology_term_id":"MONDO:0005148"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"mesenteric artery","ontology_term_id":"UBERON:0005616","tissue_type":"tissue"}]}],"description":"Chromatin-associated RNA (caRNA) has been proposed as a type of epigenomic modifier. Here, we test whether environmental stress can induce cellular dysfunction through modulating RNA-chromatin interactions. We induce endothelial cell (EC) dysfunction with high glucose and TNF\u03b1 (H\u2009+\u2009T), that mimic the common stress in diabetes mellitus. We characterize the H\u2009+\u2009T-induced changes in gene expression by single cell (sc)RNA-seq, DNA interactions by Hi-C, and RNA-chromatin interactions by iMARGI. H\u2009+\u2009T induce inter-chromosomal RNA-chromatin interactions, particularly among the super enhancers. To test the causal relationship between H\u2009+\u2009T-induced RNA-chromatin interactions and the expression of EC dysfunction-related genes, we suppress the LINC00607 RNA. This suppression attenuates the expression of SERPINE1, a critical pro-inflammatory and pro-fibrotic gene. Furthermore, the changes of the co-expression gene network between diabetic and healthy donor-derived ECs corroborate the H\u2009+\u2009T-induced RNA-chromatin interactions. Taken together, caRNA-mediated dysregulation of gene expression modulates EC dysfunction, a crucial mechanism underlying numerous diseases.","doi":"10.1038/s41467-020-18957-w","is_pre_analysis":false,"links":[{"link_name":"GSE135357","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE135357"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/87d52a86-bdc7-440c-b84d-170f7dc346d9"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Zhong-Lab-UCSD/NCOMMS-19-24818"}],"name":"Stress-induced RNA\u2013chromatin interactions promote endothelial dysfunction","published_at":"2021-05-06T16:41:21+00:00","publisher_metadata":{"authors":[{"family":"Calandrelli","given":"Riccardo"},{"family":"Xu","given":"Lixia"},{"family":"Luo","given":"Yingjun"},{"family":"Wu","given":"Weixin"},{"family":"Fan","given":"Xiaochen"},{"family":"Nguyen","given":"Tri"},{"family":"Chen","given":"Chien-Ju"},{"family":"Sriram","given":"Kiran"},{"family":"Tang","given":"Xiaofang"},{"family":"Burns","given":"Andrew B."},{"family":"Natarajan","given":"Rama"},{"family":"Chen","given":"Zhen Bouman"},{"family":"Zhong","given":"Sheng"}],"is_preprint":false,"journal":"Nat Commun","published_at":1606780800.0,"published_day":1,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:54:39+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c672834e-c3e3-49cb-81a5-4c844be4a975","collection_url":"https://cellxgene.cziscience.com/collections/c672834e-c3e3-49cb-81a5-4c844be4a975","collection_version_id":"1efed4ad-e5c6-48c7-aab6-9e9956d3ab41","consortia":[],"contact_email":"jessica.neely@ucsf.edu","contact_name":"Jessica Neely","created_at":"2026-06-10T13:57:28+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a199ca73-035d-44e2-9893-4c493151db21","dataset_version_id":"25c3842d-81c5-49d4-99ce-3ca37ff6e00d","disease":[{"label":"juvenile dermatomyositis","ontology_term_id":"MONDO:0008054"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Juvenile Dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I interferon response and autoantibodies. Treatment options are limited due to incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of JDM patients at different stages of disease activity using single-cell transcriptomics paired with surface protein expression. By immunophenotyping peripheral blood mononuclear cells, we observed skewing of the B cell compartment towards an immature naive state as a hallmark of JDM at diagnosis. Furthermore, we find that these changes in B cells are paralleled by T cell signatures suggestive of Th2-mediated inflammation that persist despite disease quiescence. We applied network analysis to reveal that hyperactivation of the type I interferon response in all immune populations is coordinated with previously masked cell states including dysfunctional protein processing in CD4+ T cells and regulation of cell death programming in NK, CD8+ T cells and gdT cells. Together, these findings unveil the coordinated immune dysregulation underpinning JDM and provide insight into strategies for restoring balance in immune function.","doi":"10.1172/jci.insight.176963","is_pre_analysis":false,"links":[],"name":"CITEseq of JDM PBMCs","published_at":"2024-05-23T23:57:17+00:00","publisher_metadata":{"authors":[{"family":"Rabadam","given":"Gabrielle"},{"family":"Wibrand","given":"Camilla"},{"family":"Flynn","given":"Emily"},{"family":"Hartoularos","given":"George C."},{"family":"Sun","given":"Yang"},{"family":"Madubata","given":"Chioma"},{"family":"Fragiadakis","given":"Gabriela K."},{"family":"Ye","given":"Chun Jimmie"},{"family":"Kim","given":"Susan"},{"family":"Gartner","given":"Zev J."},{"family":"Sirota","given":"Marina"},{"family":"Neely","given":"Jessica"}],"is_preprint":false,"journal":"JCI Insight","published_at":1719187200.0,"published_day":24,"published_month":6,"published_year":2024},"revised_at":"2026-06-11T16:54:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d86517f0-fa7e-4266-b82e-a521350d6d36","collection_url":"https://cellxgene.cziscience.com/collections/d86517f0-fa7e-4266-b82e-a521350d6d36","collection_version_id":"c71d47f4-2607-47f3-8512-216c9493d7d0","consortia":[],"contact_email":"lukas.steuernagel@sf.mpg.de","contact_name":"Lukas Steuernagel","created_at":"2026-06-10T01:22:22+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"dbb4e1ed-d820-4e83-981f-88ef7eb55a35","dataset_version_id":"87b802cc-73ca-422a-8cc7-6d6d38449b3f","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"hypothalamus","ontology_term_id":"UBERON:0001898","tissue_type":"tissue"}]}],"description":"The hypothalamus plays a key role in coordinating fundamental body functions. Despite recent progress in single-cell technologies, a unified catalogue and molecular characterization of the heterogeneous cell types and, specifically, neuronal subtypes in this brain region are still lacking. Here we present an integrated reference atlas \u201cHypoMap\u201d of the murine hypothalamus consisting of 384,925 cells, with the ability to incorporate new additional experiments. We validate HypoMap by comparing data collected from SmartSeq2 and bulk RNA sequencing of selected neuronal cell types with different degrees of cellular heterogeneity.\nPlease click on the blue cells below to explore the data.","doi":"10.1038/s42255-022-00657-y","is_pre_analysis":false,"links":[{"link_name":"GSE132355","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132355"},{"link_name":"GSE193921","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE193921"},{"link_name":"GSE132730","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132730"},{"link_name":"GSE207736","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE207736"},{"link_name":"GSE113576","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE113576"},{"link_name":"GSE172204","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE172204"},{"link_name":"SRP135960","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/SRP135960"},{"link_name":"GSE167927","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167927"},{"link_name":"GSE172461","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE172461"},{"link_name":"GSE130597","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE130597"},{"link_name":"GSE132608","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132608"},{"link_name":"GSE119960","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE119960"},{"link_name":"GSE93374","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE93374"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://data.mendeley.com/datasets/ypx3sw2f7c/3"},{"link_name":"GSE125065","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE125065"},{"link_name":"GSE117295","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117295"},{"link_name":"GSE146692","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146692"},{"link_name":"GSE87544","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE87544"}],"name":"HypoMap \u2013 a unified single cell gene expression atlas of the murine hypothalamus","published_at":"2022-10-24T23:20:01+00:00","publisher_metadata":{"authors":[{"family":"Steuernagel","given":"Lukas"},{"family":"Lam","given":"Brian Y. H."},{"family":"Klemm","given":"Paul"},{"family":"Dowsett","given":"Georgina K. C."},{"family":"Bauder","given":"Corinna A."},{"family":"Tadross","given":"John A."},{"family":"Hitschfeld","given":"Tamara Sotelo"},{"family":"del Rio Martin","given":"Almudena"},{"family":"Chen","given":"Weiyi"},{"family":"de Solis","given":"Alain J."},{"family":"Fenselau","given":"Henning"},{"family":"Davidsen","given":"Peter"},{"family":"Cimino","given":"Irene"},{"family":"Kohnke","given":"Sara N."},{"family":"Rimmington","given":"Debra"},{"family":"Coll","given":"Anthony P."},{"family":"Beyer","given":"Andreas"},{"family":"Yeo","given":"Giles S. H."},{"family":"Br\u00fcning","given":"Jens C."}],"is_preprint":false,"journal":"Nat Metab","published_at":1666224000.0,"published_day":20,"published_month":10,"published_year":2022},"revised_at":"2026-06-11T16:54:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"2bebc4ae-69a2-4001-9d2f-091ec9b4020c","collection_url":"https://cellxgene.cziscience.com/collections/2bebc4ae-69a2-4001-9d2f-091ec9b4020c","collection_version_id":"779a2d25-2592-4e70-ac90-c9ca24cf9cc3","consortia":["Human Cell Atlas (HCA)"],"contact_email":"nicolo.caporale@unimi.it","contact_name":"Nicol\u00f2 Caporale","created_at":"2026-06-10T20:05:46+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lamina propria of large intestine","ontology_term_id":"UBERON:0011189","tissue_type":"tissue"},{"label":"lamina propria of small intestine","ontology_term_id":"UBERON:0001238","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"83caa705-a765-4f99-9bf2-1d8b01674104","dataset_version_id":"029ecf44-8aeb-4931-b5e8-5f40fd6c0e72","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lamina propria of large intestine","ontology_term_id":"UBERON:0011189","tissue_type":"tissue"},{"label":"lamina propria of small intestine","ontology_term_id":"UBERON:0001238","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"4e6eb9d1-5de7-43ac-b931-21995be65c10","dataset_version_id":"7b0e6dc4-0897-4116-b437-938e7fcd66cd","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lamina propria of large intestine","ontology_term_id":"UBERON:0011189","tissue_type":"tissue"},{"label":"lamina propria of small intestine","ontology_term_id":"UBERON:0001238","tissue_type":"tissue"}]}],"description":"The intestinal mucosa is composed of a cell monolayer of epithelial cells and the underlying lamina propria, a connective tissue layer that hosts most of the intestinal immune cells and is the main local immune effector site. This cell atlas comprises cells from the human intestinal lamina propria, which were collected from tissue resections of patients undergoing surgery due to intestinal neoplasia. The biological tissues used in this study were adjacent to the intestinal neoplasms and macroscopically disease-free. Using a recently published protocol (DOI: https://doi.org/10.1038/s41596-020-00482-1) for intestinal tissue layer separation, we generated single cell RNA sequencing datasets from the small and large intestinal lamina propria as well as the underlying submucosa, both devoid of gut-associated lymphoid tissues. Our datasets contain (I) Epcam-CD45- stromal cells (2 donors, ~ 32926 cells), (II) Epcam-CD45-CD31- stromal cells (1 donor, ~ 34044 cells) as well as sorted (III) CD45+HLA-DR+CD3-CD19- antigen-presenting cells (6 donors, ~ 28750 cells). Together, our data constitutes a cellular census of the intestinal antigen-presenting cells as well as the tissue-resident stromal compartment, which can be used as a resource to explore the diversity, functions and potential interactions of these cells during homeostasis.","doi":"10.1126/sciimmunol.adz8650","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://doi.org/10.1038/s41596-020-00482-1"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/LineWulff/FentonWulff_LP_MNP"},{"link_name":"GSE309239","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE309239"}],"name":"Cell atlas of antigen-presenting and stromal cells from the human intestine","published_at":"2026-04-29T21:10:48+00:00","publisher_metadata":{"authors":[{"family":"Fenton","given":"Thomas M."},{"family":"Wulff","given":"Line"},{"family":"V\u00e4\u00e4n\u00e4nen","given":"Venla"},{"family":"Jones","given":"Gareth-Rhys"},{"family":"Lemvigh","given":"Camilla Koldb\u00e6k"},{"family":"Riis","given":"Lene B."},{"family":"Wewer","given":"Mads Damsgaard"},{"family":"Vandamme","given":"Julien"},{"family":"J\u00f8rgensen","given":"Peter B."},{"family":"Bain","given":"Calum C."},{"family":"Belling","given":"Kirstine G."},{"family":"Ho","given":"Gwo-Tzer"},{"family":"Pers","given":"Tune H."},{"family":"Poulsen","given":"Anja"},{"family":"Madsen","given":"Gorm R."},{"family":"Nielsen","given":"Ole H."},{"family":"Jakobsen","given":"Henrik L."},{"family":"Izarzugaza","given":"Jose MG."},{"family":"Bendtsen","given":"Flemming"},{"family":"Brunak","given":"S\u00f8ren"},{"family":"Mowat","given":"Allan M."},{"family":"Olsen","given":"Lars R."},{"family":"M\u00f6rbe","given":"Urs"},{"family":"Agace","given":"William W."}],"is_preprint":false,"journal":"Sci. Immunol.","published_at":1765497600.0,"published_day":12,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:54:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"61e422dd-c9cd-460e-9b91-72d9517348ef","collection_url":"https://cellxgene.cziscience.com/collections/61e422dd-c9cd-460e-9b91-72d9517348ef","collection_version_id":"0c23706f-3628-4cd4-9389-de2c75db1099","consortia":[],"contact_email":"arul@med.umich.edu","contact_name":"Arul M. 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Despite their success, the efficacy of these treatments is variable across patients and cancer types. Numerous single-cell RNA-sequencing (scRNA-seq) studies have been conducted to unravel cell-specific responses to ICB treatment. However, these studies are limited in their sample sizes and require advanced coding skills for exploration. Here, we have compiled eight scRNA-seq datasets from nine cancer types, encompassing 223 patients, 90,270 cancer cells, and 265,673 other cell types. This compilation forms a unique resource tailored for investigating how cancer cells respond to ICB treatment across cancer types. We meticulously curated, quality-checked, pre-processed, and analyzed the data, ensuring easy access for researchers. Moreover, we designed a user-friendly interface for seamless exploration. By sharing the code and data for creating these interfaces, we aim to assist fellow researchers. These resources offer valuable support to those interested in leveraging and exploring single-cell datasets across diverse cancer types, facilitating a comprehensive understanding of ICB responses.","doi":"10.1038/s41597-025-04381-6","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/MahnoorNGondal/scRNA-seq-ICB-cohorts"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/10407126"}],"name":"Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients","published_at":"2025-01-24T20:58:43+00:00","publisher_metadata":{"authors":[{"family":"Gondal","given":"Mahnoor N."},{"family":"Cieslik","given":"Marcin"},{"family":"Chinnaiyan","given":"Arul M."}],"is_preprint":false,"journal":"Sci Data","published_at":1737504000.0,"published_day":22,"published_month":1,"published_year":2025},"revised_at":"2026-06-11T16:55:55+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"24e324a1-b42d-4438-9bb5-cf5233fa90b0","collection_url":"https://cellxgene.cziscience.com/collections/24e324a1-b42d-4438-9bb5-cf5233fa90b0","collection_version_id":"486a1b4e-bf5b-4322-ac5d-e8d16c4cdee0","consortia":[],"contact_email":"jal2063@med.cornell.edu","contact_name":"James Lo","created_at":"2026-06-10T01:23:08+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7b6bab5a-f9c4-4a56-9ed4-3b9079b14867","dataset_version_id":"3ae58a8e-a64e-44b5-94c6-af55c88e02d3","disease":[{"label":"myocardial infarction","ontology_term_id":"MONDO:0005068"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"heart","ontology_term_id":"UBERON:0000948","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"liver","ontology_term_id":"UBERON:0002107","tissue_type":"tissue"},{"label":"pancreas","ontology_term_id":"UBERON:0001264","tissue_type":"tissue"}]}],"description":"Mice respond to myocardial infarction (MI) by generating a fibrotic scar in the heart. This is accompanied by systemic inflammation after the MI resolves. In contrast, zebrafish can fully regenerate their heart after heart injury. To further investigate the divergent species\u2019 responses to cardiac injury, single cell transcriptomic analyses were performed on the heart, blood, liver, kidney, and pancreatic islets.","doi":"10.1038/s42003-024-07315-x","is_pre_analysis":false,"links":[{"link_name":"GSE227191","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227191"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/abcwcm/CZI_MI_mouseZebrafish"}],"name":"Single cell transcriptomic analyses of the dynamic local and systemic response to cardiac injury in mice and zebrafish.","published_at":"2024-12-02T21:48:15+00:00","publisher_metadata":{"authors":[{"family":"Cortada","given":"Eric"},{"family":"Yao","given":"Jun"},{"family":"Xia","given":"Yu"},{"family":"D\u00fcndar","given":"Friederike"},{"family":"Zumbo","given":"Paul"},{"family":"Yang","given":"Boris"},{"family":"Rubio-Navarro","given":"Alfonso"},{"family":"Perder","given":"Bj\u00f6rn"},{"family":"Qiu","given":"Miaoyan"},{"family":"Pettinato","given":"Anthony M."},{"family":"Homan","given":"Edwin A."},{"family":"Stoll","given":"Lisa"},{"family":"Betel","given":"Doron"},{"family":"Cao","given":"Jingli"},{"family":"Lo","given":"James C."}],"is_preprint":false,"journal":"Commun 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Here, we develop a targeted single nuclear RNA sequencing approach and use it to identify an array of cholinergic interneurons, visceral and skeletal motor neurons. Our data expose markers for distinguishing these classes of cholinergic neurons and their rich diversity. Specifically, visceral motor neurons, which provide autonomic control, can be divided into more than a dozen transcriptomic classes with anatomically restricted localization along the spinal cord. The complexity of the skeletal motor neurons is also reflected in our analysis with alpha, gamma, and a third subtype, possibly corresponding to the elusive beta motor neurons, clearly distinguished. In combination, our data provide a comprehensive transcriptomic description of this important population of neurons that control many aspects of physiology and movement and encompass the cellular substrates for debilitating degenerative disorders.","doi":"10.1038/s41467-021-22691-2","is_pre_analysis":false,"links":[],"name":"Single nucleus RNA-sequencing defines unexpected diversity of cholinergic neuron types in the adult mouse spinal cord","published_at":"2026-01-09T18:24:52+00:00","publisher_metadata":{"authors":[{"family":"Alkaslasi","given":"Mor R."},{"family":"Piccus","given":"Zoe E."},{"family":"Hareendran","given":"Sangeetha"},{"family":"Silberberg","given":"Hanna"},{"family":"Chen","given":"Li"},{"family":"Zhang","given":"Yajun"},{"family":"Petros","given":"Timothy J."},{"family":"Le Pichon","given":"Claire E."}],"is_preprint":false,"journal":"Nat Commun","published_at":1619740800.0,"published_day":30,"published_month":4,"published_year":2021},"revised_at":"2026-06-11T16:54:45+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"62ef75e4-cbea-454e-a0ce-998ec40223d3","collection_url":"https://cellxgene.cziscience.com/collections/62ef75e4-cbea-454e-a0ce-998ec40223d3","collection_version_id":"1217c1b3-4a9c-4e90-baeb-1f67a043709a","consortia":["CZI Cell Science","Wellcome HCA Strategic Science Support"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. 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cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a dataset of ~360,000 cells. To systematically resolve immune cell heterogeneity across tissues, we developed CellTypist, a machine learning tool for rapid and precise cell type annotation. Using this approach, combined with detailed curation, we determined the tissue distribution of finely phenotyped immune cell types, revealing hitherto unappreciated tissue-specific features and clonal architecture of T and B cells. Our multitissue approach lays the foundation for identifying highly resolved immune cell types by leveraging a common reference dataset, tissue-integrated expression analysis, and antigen receptor sequencing.","doi":"10.1126/science.abl5197","is_pre_analysis":false,"links":[{"link_name":"E-MTAB-11536","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11536"},{"link_name":"","link_type":"OTHER","link_url":"http://pan-immune.cells.ucsc.edu/"},{"link_name":"","link_type":"OTHER","link_url":"https://www.celltypist.org/"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1845"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/04e4292c-f62f-4098-ae9b-fd69ae002a90"}],"name":"Cross-tissue immune cell analysis reveals tissue-specific features in humans","published_at":"2022-05-13T09:00:38+00:00","publisher_metadata":{"authors":[{"family":"Dom\u00ednguez Conde","given":"C."},{"family":"Xu","given":"C."},{"family":"Jarvis","given":"L. 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A."},{"family":"James","given":"L. K."},{"family":"Meyer","given":"K. B."},{"family":"Yosef","given":"N."},{"family":"Clatworthy","given":"M. R."},{"family":"Sims","given":"P. A."},{"family":"Farber","given":"D. L."},{"family":"Saeb-Parsy","given":"K."},{"family":"Jones","given":"J. L."},{"family":"Teichmann","given":"S. A."}],"is_preprint":false,"journal":"Science","published_at":1652400000.0,"published_day":13,"published_month":5,"published_year":2022},"revised_at":"2026-06-11T16:54:49+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"92db8a7e-8761-4317-873f-15606c016ce5","collection_url":"https://cellxgene.cziscience.com/collections/92db8a7e-8761-4317-873f-15606c016ce5","collection_version_id":"9526e224-ded6-40f2-8216-8d204cb7da90","consortia":[],"contact_email":"ktlim492@korea.ac.kr","contact_name":"Kyungtae Lim","created_at":"2026-06-10T16:09:10+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"781cc817-3fd0-487c-a55a-b47b2786a05d","dataset_version_id":"89a17e6a-bbb0-4a9a-b2b4-3bafd89277a8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"organoid"}]}],"description":"Alveolar type 2 (AT2) cells maintain lung health by acting as stem cells and producing pulmonary surfactant. AT2 dysfunction underlies many lung diseases including interstitial lung disease (ILD), in which some inherited forms result from mislocalisation of surfactant protein C (SFTPC) variants. Disease modelling and dissection of mechanisms remains challenging due to complexities in deriving and maintaining human AT2 cells ex vivo. Here, we describe the development of mature, expandable AT2    organoids derived from human fetal lungs which are phenotypically stable, can differentiate into AT1-like cells and are genetically manipulable. We use these organoids to test key effectors of SFTPC maturation identified in a forward genetic screen including the E3 ligase ITCH, demonstrating that their depletion phenocopies the pathological SFTPC redistribution seen for the SFTPC-I73T variant. In summary, we demonstrate the development of a novel alveolar organoid model and use it to identify effectors of SFTPC maturation necessary for AT2 health.","doi":"10.1038/s44318-024-00328-6","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Peng-He-Lab/2024_AT2_organoids"},{"link_name":"GSE237359","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE237359"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://www.ebi.ac.uk/biostudies/sourcedata/studies/S-SCDT-10_1038-S44318-024-00328-6"}],"name":"A novel human fetal lung-derived alveolar organoid model reveals mechanisms of surfactant protein C maturation relevant to interstitial lung disease","published_at":"2025-05-16T16:39:16+00:00","publisher_metadata":{"authors":[{"family":"Lim","given":"Kyungtae"},{"family":"Rutherford","given":"Eimear N"},{"family":"Delpiano","given":"Livia"},{"family":"He","given":"Peng"},{"family":"Lin","given":"Weimin"},{"family":"Sun","given":"Dawei"},{"family":"Van den Boomen","given":"Dick J H"},{"family":"Edgar","given":"James R"},{"family":"Bang","given":"Jae Hak"},{"family":"Predeus","given":"Alexander"},{"family":"Teichmann","given":"Sarah A"},{"family":"Marioni","given":"John C"},{"family":"Matesic","given":"Lydia E"},{"family":"Lee","given":"Joo-Hyeon"},{"family":"Lehner","given":"Paul J"},{"family":"Marciniak","given":"Stefan J"},{"family":"Rawlins","given":"Emma L"},{"family":"Dickens","given":"Jennifer A"}],"is_preprint":false,"journal":"EMBO J","published_at":1736899200.0,"published_day":15,"published_month":1,"published_year":2025},"revised_at":"2026-06-11T16:54:50+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"741abcf7-af4b-425d-88db-7e0b0d845719","collection_url":"https://cellxgene.cziscience.com/collections/741abcf7-af4b-425d-88db-7e0b0d845719","collection_version_id":"088910d6-3530-4a62-ade4-478412900a90","consortia":[],"contact_email":"nryba@dir.nidcr.nih.gov","contact_name":"Nick Ryba","created_at":"2026-06-10T04:46:34+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d973ea15-3722-4bc8-a0e8-1d956d26e203","dataset_version_id":"cf1271ef-08be-46dd-b39e-90c3aa72755e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dorsal root ganglion","ontology_term_id":"UBERON:0000044","tissue_type":"tissue"}]}],"description":"Somatosensory neurons with cell bodies in the dorsal root ganglia (DRG) project to the skin, muscles, bones, and viscera to detect touch and temperature as well as to mediate proprioception and many types of interoception. In addition, the somatosensory system conveys the clinically relevant noxious sensations of pain and itch. Here, we used single nuclear transcriptomics to characterize transcriptomic classes of human DRG neurons that detect these diverse types of stimuli. Notably, multiple types of human DRG neurons have transcriptomic features that resemble their mouse counterparts although expression of genes considered important for sensory function often differed between species. More unexpectedly, we identified several transcriptomic classes with no clear equivalent in the other species. This dataset should serve as a valuable resource for the community, for example as means of focusing translational efforts on molecules with conserved expression across species.","doi":"10.7554/eLife.71752","is_pre_analysis":false,"links":[{"link_name":"GSE168243","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168243"},{"link_name":"PMC8626086","link_type":"OTHER","link_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC8626086/"}],"name":"Single-nucleus transcriptomic analysis of human dorsal root ganglion neurons.","published_at":"2025-03-20T17:29:30+00:00","publisher_metadata":{"authors":[{"family":"Nguyen","given":"Minh Q"},{"family":"von Buchholtz","given":"Lars J"},{"family":"Reker","given":"Ashlie N"},{"family":"Ryba","given":"Nicholas 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Samples from a single time point per subject were profiled using scRNA-seq at the Allen Institute for Immunology to complement the longitudinal profiling of young and older adults in the study \"Multi-omic profiling reveals age-related immune dynamics in healthy adults.\u201d We provide additional interactive tools and downloads for exploring both this cross-sectional and the longitudinally profiled cohorts at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/.","doi":"10.1038/s41586-025-09686-5","is_pre_analysis":false,"links":[{"link_name":"Dynamics of Human Immune Health and Age","link_type":"OTHER","link_url":"https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/"},{"link_name":"GSE275067","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE275067"},{"link_name":"Dynamics of IHA Collection","link_type":"OTHER","link_url":"https://cellxgene.cziscience.com/collections/e9360edf-b0b7-4e01-bce8-e596814f13e7"}],"name":"Immunobiology of Aging Cohort PBMC Profiling","published_at":"2026-02-10T19:15:17+00:00","publisher_metadata":{"authors":[{"family":"Gong","given":"Qiuyu"},{"family":"Sharma","given":"Mehul"},{"family":"Glass","given":"Marla C."},{"family":"Kuan","given":"Emma L."},{"family":"Chander","given":"Aishwarya"},{"family":"Singh","given":"Mansi"},{"family":"Graybuck","given":"Lucas T."},{"family":"Thomson","given":"Zachary J."},{"family":"LaFrance","given":"Christian M."},{"family":"Rachid Zaim","given":"Samir"},{"family":"Peng","given":"Tao"},{"family":"Okada","given":"Lauren Y."},{"family":"Genge","given":"Palak C."},{"family":"Henderson","given":"Katherine E."},{"family":"Dornisch","given":"Elisabeth M."},{"family":"Layton","given":"Erik D."},{"family":"Wittig","given":"Peter J."},{"family":"Heubeck","given":"Alexander T."},{"family":"Mukuka","given":"Nelson M."},{"family":"Reading","given":"Julian"},{"family":"Strawn","given":"Garrett"},{"family":"Titus-Adewunmi","given":"Teminijesu"},{"family":"Abadie","given":"Kathleen"},{"family":"Roll","given":"Charles R."},{"family":"Hernandez","given":"Veronica"},{"family":"Parthasarathy","given":"Vaishnavi"},{"family":"Stuckey","given":"Tyanna J."},{"family":"Musgrove","given":"Blessing"},{"family":"Swanson","given":"Elliott"},{"family":"Lord","given":"Cara"},{"family":"Weiss","given":"Morgan D. 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HPV-negative HNSCCs have a high recurrence rate, and individual patients\u2019 responses to treatment vary greatly due to the high level of cellular heterogeneity of the tumor and its microenvironment. Here, we describe a HPV-negative HNSCC single cell atlas, which we created by integrating six publicly available datasets encompassing over 230,000 cells across 54 patients. We classify cell types, subpopulations, and their expression programs in the immune, mesenchymal, endothelial and epithelial compartments. We interrogate the relationship between cell types through hierarchical clustering, cell-cell communication analysis and correlating populations changing together across patients. We resolve the myeloid and fibroblast compartments, revealing an IL1B+ myeloid population previously unexplored in HNSCC and clarifying two immune cancer associated fibroblast populations that are frequently conflated, identify sex-associated changes in cell type proportions, and a unique interaction between CXCL8-positive fibroblasts and vascular endothelial cells.  We utilize the atlas to contextualize the relationships between existing signatures and cell populations, harmonize nomenclature across studies, and show the power of this large-scale resource to robustly identify associations between transcriptional signatures and clinical phenotypes that would not be possible to discover using fewer patients. Beyond our findings, the atlas serves as a public resource for the high-resolution characterization of tumor heterogeneity of HPV-negative HNSCC.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/montilab/kroehling_et_al_hpvneg_hnscc_atlas"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/17880437"}],"name":"A highly resolved integrated single-cell atlas of HPV-negative Head and Neck Cancer","published_at":"2026-02-02T22:01:09+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:55:09+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d17249d2-0e6e-4500-abb8-e6c93fa1ac6f","collection_url":"https://cellxgene.cziscience.com/collections/d17249d2-0e6e-4500-abb8-e6c93fa1ac6f","collection_version_id":"a098fbf9-5cfb-4126-b928-9acca6552be8","consortia":["Allen Institute for Brain Science","BRAIN Initiative"],"contact_email":"trygveb@alleninstitute.org","contact_name":"Trygve E. 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Single cell transcriptomics enables higher-resolution characterization of cell types in human cortex, which we used to revisit the idea of the canonical cortical microcircuit and to understand functional areal specialization. Deeply sampled single nucleus RNA-sequencing of eight cortical areas spanning cortical structural variation showed highly consistent cellular makeup for 24 coarse cell subclasses. However, proportions of excitatory neuron subclasses varied strikingly, reflecting differences in intra- and extracortical connectivity across primary sensorimotor and association cortices. Astrocytes and oligodendrocytes also showed differences in laminar organization across areas. Primary visual cortex showed dramatically different organization, including major differences in the ratios of excitatory to inhibitory neurons, expansion of layer 4 excitatory neuron types and specialized inhibitory neurons. Finally, gene expression variation in conserved neuron subclasses predicts differences in synaptic function across areas. Together these results provide a refined cellular and molecular characterization of human cortical cytoarchitecture that reflects functional connectivity and predicts areal specialization.","doi":"10.1126/science.adf6812","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/AllenInstitute/human_cross_areal"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-rg2rc5m"},{"link_name":"","link_type":"OTHER","link_url":"https://portal.brain-map.org/atlases-and-data/rnaseq/human-multiple-cortical-areas-smart-seq"}],"name":"Transcriptomic cytoarchitecture reveals principles of human neocortex organization","published_at":"2023-10-20T17:46:20+00:00","publisher_metadata":{"authors":[{"family":"Jorstad","given":"Nikolas L."},{"family":"Close","given":"Jennie"},{"family":"Johansen","given":"Nelson"},{"family":"Yanny","given":"Anna Marie"},{"family":"Barkan","given":"Eliza R."},{"family":"Travaglini","given":"Kyle J."},{"family":"Bertagnolli","given":"Darren"},{"family":"Campos","given":"Jazmin"},{"family":"Casper","given":"Tamara"},{"family":"Crichton","given":"Kirsten"},{"family":"Dee","given":"Nick"},{"family":"Ding","given":"Song-Lin"},{"family":"Gelfand","given":"Emily"},{"family":"Goldy","given":"Jeff"},{"family":"Hirschstein","given":"Daniel"},{"family":"Kiick","given":"Katelyn"},{"family":"Kroll","given":"Matthew"},{"family":"Kunst","given":"Michael"},{"family":"Lathia","given":"Kanan"},{"family":"Long","given":"Brian"},{"family":"Martin","given":"Naomi"},{"family":"McMillen","given":"Delissa"},{"family":"Pham","given":"Trangthanh"},{"family":"Rimorin","given":"Christine"},{"family":"Ruiz","given":"Augustin"},{"family":"Shapovalova","given":"Nadiya"},{"family":"Shehata","given":"Soraya"},{"family":"Siletti","given":"Kimberly"},{"family":"Somasundaram","given":"Saroja"},{"family":"Sulc","given":"Josef"},{"family":"Tieu","given":"Michael"},{"family":"Torkelson","given":"Amy"},{"family":"Tung","given":"Herman"},{"family":"Callaway","given":"Edward M."},{"family":"Hof","given":"Patrick R."},{"family":"Keene","given":"C. 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Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 donors, spanning 7 population groups across 5 Asian countries, and 6 controls. Though population groups are frequently compared at the continental level, we found that sub-continental diversity, age, and sex pervasively impacted cellular and molecular properties of immune cells. These included differential abundance of cell neighbourhoods, as well as cell populations and genes relevant to disease risk, pathogenesis, and diagnostics. We discovered functional genetic variants influencing cell type-specific gene expression which were under-represented in non-Asian populations, and helped contextualise disease-associated variants. AIDA enables analyses of multi-ancestry disease datasets and facilitates the development of precision medicine efforts in Asia and beyond.\n\nPlease note that the AIDA Phase 1 Data Freeze v1 object comprises 1,058,909 peripheral blood mononuclear cells from 503 healthy donors from Japan, Singapore, and South Korea alongside common controls. This first AIDA data freeze was released to the research community pre-publication, and was also part of the first CZ CELLxGENE Census assembled in May 2023. Going from Data Freeze v1 to Data Freeze v2, we added additional healthy Asian donor samples and control samples - please see our publications for further details.","doi":"10.1016/j.cell.2025.02.017","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/f0f89c14-7460-4bab-9d42-22228a91f185"},{"link_name":"Github code","link_type":"OTHER","link_url":"https://github.com/prabhakarlab/AIDA_Phase1/"},{"link_name":"Zenodo code","link_type":"OTHER","link_url":"https://zenodo.org/records/14722572"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/35d5b057-3daf-4ccd-8112-196194598893"},{"link_name":"","link_type":"OTHER","link_url":"https://celltype.info/project/336/dataset/591"}],"name":"Asian Immune Diversity Atlas (AIDA)","published_at":"2023-05-04T19:04:24+00:00","publisher_metadata":{"authors":[{"family":"Kock","given":"Kian Hong"},{"family":"Tan","given":"Le Min"},{"family":"Han","given":"Kyung Yeon"},{"family":"Ando","given":"Yoshinari"},{"family":"Jevapatarakul","given":"Damita"},{"family":"Chatterjee","given":"Ankita"},{"family":"Lin","given":"Quy Xiao Xuan"},{"family":"Buyamin","given":"Eliora Violain"},{"family":"Sonthalia","given":"Radhika"},{"family":"Rajagopalan","given":"Deepa"},{"family":"Tomofuji","given":"Yoshihiko"},{"family":"Sankaran","given":"Shvetha"},{"family":"Park","given":"Mi-So"},{"family":"Abe","given":"Mai"},{"family":"Chantaraamporn","given":"Juthamard"},{"family":"Furukawa","given":"Seiko"},{"family":"Ghosh","given":"Supratim"},{"family":"Inoue","given":"Gyo"},{"family":"Kojima","given":"Miki"},{"family":"Kouno","given":"Tsukasa"},{"family":"Lim","given":"Jinyeong"},{"family":"Myouzen","given":"Keiko"},{"family":"Nguantad","given":"Sarintip"},{"family":"Oh","given":"Jin-Mi"},{"family":"Rayan","given":"Nirmala Arul"},{"family":"Sarkar","given":"Sumanta"},{"family":"Suzuki","given":"Akari"},{"family":"Thungsatianpun","given":"Narita"},{"family":"Venkatesh","given":"Prasanna Nori"},{"family":"Moody","given":"Jonathan"},{"family":"Nakano","given":"Masahiro"},{"family":"Chen","given":"Ziyue"},{"family":"Tian","given":"Chi"},{"family":"Zhang","given":"Yuntian"},{"family":"Tong","given":"Yihan"},{"family":"Tan","given":"Crystal T.Y."},{"family":"Tizazu","given":"Anteneh Mehari"},{"family":"Loh","given":"Marie"},{"family":"Hwang","given":"You Yi"},{"family":"Ho","given":"Roger C."},{"family":"Larbi","given":"Anis"},{"family":"Ng","given":"Tze Pin"},{"family":"Won","given":"Hong-Hee"},{"family":"Wright","given":"Fred A."},{"family":"Villani","given":"Alexandra-Chlo\u00e9"},{"family":"Park","given":"Jong-Eun"},{"family":"Choi","given":"Murim"},{"family":"Liu","given":"Boxiang"},{"family":"Maitra","given":"Arindam"},{"family":"Pithukpakorn","given":"Manop"},{"family":"Suktitipat","given":"Bhoom"},{"family":"Ishigaki","given":"Kazuyoshi"},{"family":"Okada","given":"Yukinori"},{"family":"Yamamoto","given":"Kazuhiko"},{"family":"Carninci","given":"Piero"},{"family":"Chambers","given":"John C."},{"family":"Hon","given":"Chung-Chau"},{"family":"Matangkasombut","given":"Ponpan"},{"family":"Charoensawan","given":"Varodom"},{"family":"Majumder","given":"Partha P."},{"family":"Shin","given":"Jay W."},{"family":"Park","given":"Woong-Yang"},{"family":"Prabhakar","given":"Shyam"}],"is_preprint":false,"journal":"Cell","published_at":1743465600.0,"published_day":1,"published_month":4,"published_year":2025},"revised_at":"2026-06-11T16:54:46+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"8f126edf-5405-4731-8374-b5ce11f53e82","collection_url":"https://cellxgene.cziscience.com/collections/8f126edf-5405-4731-8374-b5ce11f53e82","collection_version_id":"18748dd8-1240-434c-aaeb-18e1ea3a765e","consortia":[],"contact_email":"julian.knight@well.ox.ac.uk","contact_name":"Julian C. 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To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19. The complete raw and processed CITE-seq datasets are available at the European Genome-phenome Archive (EGA) and Zenodo respectively. Here a more limited version of the gene expression data is presented for the purpose of online visualisation and exploration of the dataset. Please note that features have been automatically filtered for compatibility with the Cellxgene Data Portal (ADT features have been removed). For further analysis it is recommended to use the unfiltered datasets from the EGA or Zenodo (where processed datasets are also available in anndata format).","doi":"10.1016/j.cell.2022.01.012","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=covid19-blood-atlas"},{"link_name":"zenodo.org","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.6120249"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001005493"},{"link_name":"Consortium Site","link_type":"OTHER","link_url":"https://www.combat.ox.ac.uk/"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/cdabcf0b-7602-4abf-9afb-3b410e545703"}],"name":"A blood atlas of COVID-19 defines hallmarks of disease severity and specificity","published_at":"2022-02-18T15:21:41+00:00","publisher_metadata":{"authors":[{"family":"Ahern","given":"David J."},{"family":"Ai","given":"Zhichao"},{"family":"Ainsworth","given":"Mark"},{"family":"Allan","given":"Chris"},{"family":"Allcock","given":"Alice"},{"family":"Angus","given":"Brian"},{"family":"Ansari","given":"M. 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Nephrectomy specimens were obtained from sites opposite from the tumour and were snap-frozen before nuclei isolation. Per library nuclei from three to five donors were pooled and demultiplexed based on genetic variants in sequencing reads. The data includes gene expression measurements of high-quality nuclei confidently mapped to an individual donor.","doi":"10.1038/s41467-025-59997-4","is_pre_analysis":false,"links":[{"link_name":"GSE254185","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE254185"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://zenodo.org/records/15124887"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/mreck1/human_kidney_multiomics"}],"name":"snRNA-seq of human kidney with ureteral obstruction","published_at":"2025-07-01T20:21:55+00:00","publisher_metadata":{"authors":[{"family":"Reck","given":"Maximilian"},{"family":"Baird","given":"David P."},{"family":"Veizades","given":"Stefan"},{"family":"Sutherland","given":"Callum"},{"family":"Bell","given":"Rachel M. 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The TM serves as the primary outflow pathway for aqueous humor, while the CB controls lens shape and produces aqueous humor. Both tissues are composed of diverse cell types, with cell abundances varying across several orders of magnitude. To create a comprehensive single-cell atlas and advance our understanding of TM and CB biology, we generated large-scale datasets from healthy human donors using single-nucleus RNA-seq (snRNA-seq), single-cell RNA-seq (scRNA-seq), and single-nucleus ATAC-seq (snATAC-seq) across a range of ages, genders, and ethnic backgrounds.\n\nAdditionally, we performed a meta-analysis by integrating previously published datasets. All data were uniformly preprocessed and combined, resulting in a comprehensive TM and CB atlas that includes transcriptomic profiles of over 1 million cells from 70 donors. We identified 19 distinct cell types, including rare populations such as immune cells, with the least abundant types representing as little as 0.08% of the total cell population. Furthermore, snATAC-seq profiling of over 500,000 nuclei provided detailed chromatin accessibility landscapes, allowing for the identification of cis-regulatory elements specific to each cell type.\n\nAll datasets are publicly accessible via CELLxGENE and the UCSC Cell Browser, enabling interactive exploration of gene expression and chromatin states at the single-cell level. As part of the Human Cell Atlas initiative, our TM and CB atlas offers a valuable resource for understanding eye physiology and establishes a foundation for further research into the cellular and molecular mechanisms regulating intraocular pressure and related ocular diseases.","doi":"10.64898/2026.06.17.732980","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://celltype.info/project/574"}],"name":"Single cell atlas of the human trabecular meshwork and ciliary body","published_at":"2025-05-05T23:34:32+00:00","publisher_metadata":{"authors":[{"family":"Jian","given":"Jinjing"},{"family":"Bao","given":"Xuan"},{"family":"Wang","given":"Jun"},{"family":"Zheng","given":"Ye"},{"family":"Li","given":"Jin"},{"family":"Shao","given":"Jianming"},{"family":"Yang","given":"Tingting"},{"family":"Yaman","given":"Ismail"},{"family":"Li","given":"Jean"},{"family":"Chen","given":"Han"},{"family":"Tolman","given":"Nicholas"},{"family":"Scheuermann","given":"Richard H."},{"family":"Zheng","given":"Jie J."},{"family":"Sheridan","given":"Carl"},{"family":"Liu","given":"Yutao"},{"family":"Du","given":"Yiqin"},{"family":"Balasubramanian","given":"Revathi"},{"family":"Zode","given":"Gulab S."},{"family":"John","given":"Simon"},{"family":"Stout","given":"J Timothy"},{"family":"Stamer","given":"Dan"},{"family":"Li","given":"Yumei"},{"family":"Chen","given":"Rui"}],"is_preprint":true,"journal":"bioRxiv","published_at":1782086400.0,"published_day":22,"published_month":6,"published_year":2026},"revised_at":"2026-06-23T16:20:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bf325905-5e8e-42e3-933d-9a9053e9af80","collection_url":"https://cellxgene.cziscience.com/collections/bf325905-5e8e-42e3-933d-9a9053e9af80","collection_version_id":"e80e3a36-7be0-4b28-a293-16016e4a0107","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"rv4@sanger.ac.uk","contact_name":"Roser Vento-Tormo","created_at":"2026-06-10T16:15:03+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"d7d7e89c-c93a-422d-8958-9b4a90b69558","dataset_version_id":"8f0c7a69-1b26-46b9-bdff-9b1715c10565","disease":[{"label":"common variable immunodeficiency","ontology_term_id":"MONDO:0015517"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"a5d95a42-0137-496f-8a60-101e17f263c8","dataset_version_id":"b8aa229e-c7fa-4e23-a3eb-a47a0c57f44a","disease":[{"label":"common variable immunodeficiency","ontology_term_id":"MONDO:0015517"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]},{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"3c75a463-6a87-4132-83a8-c3002624394d","dataset_version_id":"db2fbc4e-2764-4bee-bb4e-bc0a1cd41439","disease":[{"label":"common variable immunodeficiency","ontology_term_id":"MONDO:0015517"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, displays impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and ample phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. Here, we generate a single-cell epigenomics and transcriptomics census of na\u00efve-to-memory B cell differentiation in a CVID-discordant MZ twin pair. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B-cells mirroring defective cell-cell communication upon activation. These findings are validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in na\u00efve-to-memory B-cell transition in CVID and indicate links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, gives insight into future diagnosis and treatments of CVID patients.","doi":"10.1038/s41467-022-29450-x","is_pre_analysis":false,"links":[{"link_name":"scBS-seq data (PRJEB50820)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB50820"},{"link_name":"Smart-seq2 data, scATAC-seq data and 10x-Genomics Chromium droplet-based scRNA-seq data (EGAD00001008575)","link_type":"DATA_SOURCE","link_url":"https://ega-archive.org/datasets/EGAD00001008575"},{"link_name":"VenTo Lab","link_type":"LAB_WEBSITE","link_url":"https://ventolab.org/"},{"link_name":"Epigenetics and Immune Disease Laboratory","link_type":"LAB_WEBSITE","link_url":"https://www.carrerasresearch.org/en/epigenetics-and-immune-disease_124402"},{"link_name":"Common Variable Immunodeficiency Cell Atlas","link_type":"OTHER","link_url":"https://www.immunodeficiencycellatlas.org/"},{"link_name":"Analysis scripts","link_type":"OTHER","link_url":"https://github.com/ventolab/CVID"}],"name":"Single-cell Atlas of common variable immunodeficiency shows germinal center-associated epigenetic dysregulation in B-cell responses","published_at":"2023-02-02T13:06:43+00:00","publisher_metadata":{"authors":[{"family":"Rodr\u00edguez-Ubreva","given":"Javier"},{"family":"Arutyunyan","given":"Anna"},{"family":"Bonder","given":"Marc Jan"},{"family":"Del Pino-Molina","given":"Luc\u00eda"},{"family":"Clark","given":"Stephen J."},{"family":"de la Calle-Fabregat","given":"Carlos"},{"family":"Garcia-Alonso","given":"Luz"},{"family":"Handfield","given":"Louis-Fran\u00e7ois"},{"family":"Ciudad","given":"Laura"},{"family":"Andr\u00e9s-Le\u00f3n","given":"Eduardo"},{"family":"Krueger","given":"Felix"},{"family":"Catal\u00e0-Moll","given":"Francesc"},{"family":"Rodr\u00edguez-Cortez","given":"Virginia C."},{"family":"Polanski","given":"Krzysztof"},{"family":"Mamanova","given":"Lira"},{"family":"van Dongen","given":"Stijn"},{"family":"Kiselev","given":"Vladimir Yu."},{"family":"Mart\u00ednez-Saavedra","given":"Mar\u00eda T."},{"family":"Heyn","given":"Holger"},{"family":"Mart\u00edn","given":"Javier"},{"family":"Warnatz","given":"Klaus"},{"family":"L\u00f3pez-Granados","given":"Eduardo"},{"family":"Rodr\u00edguez-Gallego","given":"Carlos"},{"family":"Stegle","given":"Oliver"},{"family":"Kelsey","given":"Gavin"},{"family":"Vento-Tormo","given":"Roser"},{"family":"Ballestar","given":"Esteban"}],"is_preprint":false,"journal":"Nat Commun","published_at":1648771200.0,"published_day":1,"published_month":4,"published_year":2022},"revised_at":"2026-06-11T16:54:58+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"8c782494-01ed-491b-97b9-6f0d3b76c676","collection_url":"https://cellxgene.cziscience.com/collections/8c782494-01ed-491b-97b9-6f0d3b76c676","collection_version_id":"04da145a-4712-4f18-b56a-e89b582e6ec1","consortia":["Human Cell Atlas (HCA)"],"contact_email":"suvi.linna-kuosmanen@uef.fi","contact_name":"Prof. Suvi Linna-Kuosmanen","created_at":"2026-06-10T17:46:15+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f1606894-59df-4794-a37f-baa7c6fb6de1","dataset_version_id":"d070bbc4-3c71-4f7a-adaf-583ccb059eb6","disease":[{"label":"coronary artery disorder","ontology_term_id":"MONDO:0005010"},{"label":"heart valve disorder","ontology_term_id":"MONDO:0002869"},{"label":"myocardial infarction","ontology_term_id":"MONDO:0005068"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"right atrium auricular region","ontology_term_id":"UBERON:0006631","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"8f4f8502-9170-4ac2-9707-3b6985ebfe5f","dataset_version_id":"86094298-00c2-4d09-b11d-342c5aa1f951","disease":[{"label":"heart failure","ontology_term_id":"MONDO:0005252"},{"label":"heart valve disorder","ontology_term_id":"MONDO:0002869"},{"label":"myocardial ischemia","ontology_term_id":"MONDO:0024644"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"right atrium auricular region","ontology_term_id":"UBERON:0006631","tissue_type":"tissue"}]}],"description":"The CAREBANK study has enrolled patients undergoing open-heart cardiac surgery (coronary bypass surgery, operations for valvular heart disease and ascending aorta) since February 2016 at Turku University Hospital and the PERIHEART study since 2012 at Kuopio University Hospital. 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Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing.","doi":"10.1016/j.ajt.2024.08.019","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/aaronkwong/Mapping_Pulmonary_Inflammation"},{"link_name":"GSE220797","link_type":"DATA_SOURCE","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE220797"},{"link_name":"EGAS50000000490","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS50000000490"}],"name":"Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution","published_at":"2024-09-13T18:36:25+00:00","publisher_metadata":{"authors":[{"family":"Wong","given":"Aaron"},{"family":"Duong","given":"Allen"},{"family":"Wilson","given":"Gavin"},{"family":"Yeung","given":"Jonathan"},{"family":"MacParland","given":"Sonya"},{"family":"Han","given":"Hong"},{"family":"Cypel","given":"Marcelo"},{"family":"Keshavjee","given":"Shaf"},{"family":"Liu","given":"Mingyao"}],"is_preprint":false,"journal":"American Journal of Transplantation","published_at":1733011200.0,"published_day":1,"published_month":12,"published_year":2024},"revised_at":"2026-06-11T16:54:58+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"f11cb29c-b546-4738-9bd8-66ea621a7bd5","collection_url":"https://cellxgene.cziscience.com/collections/f11cb29c-b546-4738-9bd8-66ea621a7bd5","collection_version_id":"5f340a44-425e-4181-8b18-fd9a2c9b319e","consortia":[],"contact_email":"sat1003@cam.ac.uk","contact_name":"Sarah A. 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Advances in genomics and a surge in gastrointestinal diseases1,2 has fuelled efforts to catalogue cells constituting gastrointestinal tissues in health and disease3. Here we present systematic integration of 25 single-cell RNA sequencing datasets spanning the entire healthy gastrointestinal tract in development and in adulthood. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated quality control approach (scAutoQC), leading to a healthy reference atlas with approximately 1.1 million cells and 136 fine-grained cell states. We anchor 12 gastrointestinal disease datasets spanning gastrointestinal cancers, coeliac disease, ulcerative colitis and Crohn\u2019s disease to this reference. Utilizing this 1.6 million cell resource (gutcellatlas.org), we discover epithelial cell metaplasia originating from stem cells in intestinal inflammatory diseases with transcriptional similarity to cells found in pyloric and Brunner\u2019s glands. Although previously linked to mucosal healing4, we now implicate pyloric gland metaplastic cells in inflammation through recruitment of immune cells including T cells and neutrophils. Overall, we describe inflammation-induced changes in stem cells that alter mucosal tissue architecture and promote further inflammation, a concept applicable to other tissues and diseases.","doi":"10.1038/s41586-024-07571-1","is_pre_analysis":false,"links":[{"link_name":"Teichmann Lab","link_type":"LAB_WEBSITE","link_url":"https://www.teichlab.org/"},{"link_name":"E-MTAB-14050","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-14050"}],"name":"Single-cell integration reveals metaplasia in inflammatory gut diseases","published_at":"2025-10-27T18:27:39+00:00","publisher_metadata":{"authors":[{"family":"Oliver","given":"Amanda J."},{"family":"Huang","given":"Ni"},{"family":"Bartolome-Casado","given":"Raquel"},{"family":"Li","given":"Ruoyan"},{"family":"Koplev","given":"Simon"},{"family":"Nilsen","given":"Hogne R."},{"family":"Moy","given":"Madelyn"},{"family":"Cakir","given":"Batuhan"},{"family":"Polanski","given":"Krzysztof"},{"family":"Gudi\u00f1o","given":"Victoria"},{"family":"Mel\u00f3n-Ardanaz","given":"Elisa"},{"family":"Sumanaweera","given":"Dinithi"},{"family":"Dimitrov","given":"Daniel"},{"family":"Milchsack","given":"Lisa Marie"},{"family":"FitzPatrick","given":"Michael E. 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However, underlying cellular and molecular mechanisms are difficult to study in humans. We have identified an alveolar-fated epithelial progenitor in human fetal lungs, which we grow as self-organizing organoids that model key aspects of cell lineage commitment. Using this system, we have functionally validated cell-cell interactions in the developing human alveolar niche, showing that Wnt signaling from differentiating fibroblasts promotes alveolar-type-2 cell identity, whereas myofibroblasts secrete the Wnt inhibitor, NOTUM, providing spatial patterning. We identify a Wnt-NKX2.1 axis controlling alveolar differentiation. Moreover, we show that differential binding of NKX2.1 coordinates alveolar maturation, allowing us to model the effects of human genetic variation in NKX2.1 on alveolar differentiation. Our organoid system recapitulates key aspects of human fetal lung stem cell biology allowing mechanistic experiments to determine the cellular and molecular regulation of human development and disease.","doi":"10.1016/j.stem.2022.11.013","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://fetal-lung-organoid.cellgeni.sanger.ac.uk/"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-11435"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://github.com/Peng-He-Lab/2023-Late-tip-organoid"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/ERP135437"}],"name":"Organoid modeling of human fetal lung alveolar development reveals mechanisms of cell fate patterning and neonatal respiratory disease","published_at":"2025-09-16T21:13:55+00:00","publisher_metadata":{"authors":[{"family":"Lim","given":"Kyungtae"},{"family":"Donovan","given":"Alex P.A."},{"family":"Tang","given":"Walfred"},{"family":"Sun","given":"Dawei"},{"family":"He","given":"Peng"},{"family":"Pett","given":"J. 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Here, we use single cell RNA-sequencing (scRNA-seq) to define the heterogeneity of human T cells isolated from lungs, lymph nodes, bone marrow and blood, and their functional responses following stimulation. Through analysis of >50,000 resting and activated T cells, we reveal tissue T cell signatures in mucosal and lymphoid sites, and lineage-specific activation states across all sites including distinct effector states for CD8+ T cells and an interferon-response state for CD4+ T cells. Comparing scRNA-seq profiles of tumor-associated T cells to our dataset reveals predominant activated CD8+ compared to CD4+ T cell states within multiple tumor types. Our results therefore establish a high dimensional reference map of human T cell activation in health for analyzing T cells in disease.","doi":"10.1038/s41467-019-12464-3","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/simslab/cluster_diffex2018"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/simslab/scHPF"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://www.columbia.edu/~pas2182/index.php/home-top.html"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE126030"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/4a95101c-9ffc-4f30-a809-f04518a23803"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/simslab/umap_projection"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-HCAD-8"}],"name":"Single-cell transcriptomics of human T cells 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The application of high throughput single-cell technologies has provided comprehensive transcriptomic definitions of cell states within the embryo, but our knowledge of their spatial localization remains elusive. To explore early mouse organogenesis, we used Slide-seq to generate high-resolution maps of whole E8.5 and E9.5 mouse embryos. We developed sc3D, a tool for creating a three-dimensional (3D) 'digital embryo,' which allowed us to quantitatively decipher regionalized gene expression across multiple tissues. Our transcriptomic maps facilitated us to characterize gene expression patterns along the anteroposterior and dorsoventral axes, with a particular emphasis on neural tube development. We nominated and functionally characterized Prdm8, a histone methyltransferase, as a neural tube patterning gene. Furthermore, we were able to determine the transcriptional identity of ectopic neural tubes in a classical Tbx6 mutant, which provided us with additional insights into neural tube patterning. Taken together, we present a framework for a computational and experimental toolkit that enables systematic spatiotemporal dissection of complex embryonic structures via high-throughput profiling of phenotypes, thereby paving the way for the investigation of congenital and developmental abnormalities.","doi":"10.1038/s41588-023-01435-6","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.insitubiology.org/"},{"link_name":"GSE197353","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE197353"},{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/s/1c29d867bc8b90d754d2"},{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/articles/dataset/E8_5_Embryo2_h5ad/21695849/1"},{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/articles/dataset/E9_0_Embryo_h5ad/21695879/1"}],"name":"Spatial transcriptomic maps of whole mouse embryos reveal principles of neural tube patterning","published_at":"2023-09-29T17:31:37+00:00","publisher_metadata":{"authors":[{"family":"Sampath Kumar","given":"Abhishek"},{"family":"Tian","given":"Luyi"},{"family":"Bolondi","given":"Adriano"},{"family":"Hern\u00e1ndez","given":"Am\u00e8lia Aragon\u00e9s"},{"family":"Stickels","given":"Robert"},{"family":"Kretzmer","given":"Helene"},{"family":"Murray","given":"Evan"},{"family":"Wittler","given":"Lars"},{"family":"Walther","given":"Maria"},{"family":"Barakat","given":"Gabriel"},{"family":"Haut","given":"Leah"},{"family":"Elkabetz","given":"Yechiel"},{"family":"Macosko","given":"Evan Z."},{"family":"Guignard","given":"L\u00e9o"},{"family":"Chen","given":"Fei"},{"family":"Meissner","given":"Alexander"}],"is_preprint":false,"journal":"Nat Genet","published_at":1688169600.0,"published_day":1,"published_month":7,"published_year":2023},"revised_at":"2026-06-11T16:55:02+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"eeba7193-4d32-46bd-a21b-089936d60601","collection_url":"https://cellxgene.cziscience.com/collections/eeba7193-4d32-46bd-a21b-089936d60601","collection_version_id":"2ffe9f14-3ed2-477b-be24-387814c65779","consortia":[],"contact_email":"mhulsmans@mgh.harvard.edu","contact_name":"Maarten Hulsmans","created_at":"2026-06-10T17:55:56+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"87a06a2a-16c6-42f7-af1b-529fad431051","dataset_version_id":"8f01b8fa-d7ba-4417-9429-7a3a05e805f8","disease":[{"label":"atrial fibrillation || mitral valve insufficiency","ontology_term_id":"MONDO:0004981 || MONDO:1030008"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"left atrium auricular region","ontology_term_id":"UBERON:0006630","tissue_type":"tissue"}]}],"description":"Atrial fibrillation disrupts contraction of the atria, leading to stroke and heart failure. 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Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.","doi":"10.1016/j.xcrm.2023.101158","is_pre_analysis":false,"links":[{"link_name":"GSE216005","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE216005"},{"link_name":"EGAS00001006836","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001006836"}],"name":"Single cell RNA sequencing of bone marrow mononuclear cells from healthy donors and B-cell lymphoma patients following CD19 CAR T-cell therapy","published_at":"2023-06-08T19:46:29+00:00","publisher_metadata":{"authors":[{"family":"Strati","given":"Paolo"},{"family":"Li","given":"Xubin"},{"family":"Deng","given":"Qing"},{"family":"Marques-Piubelli","given":"Mario 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Becker (BMD) and Duchenne muscular dystrophy (DMD), are characterized by progressive muscle wasting, fatty replacement, fibrosis, and loss of function. To study histopathological changes, we used Visium spatial transcriptomics to profile skeletal muscle biopsies of patients affected by dystrophinopathy (n\u202f=\u202f8) and healthy controls (n\u202f=\u202f4). We estimated the proportion of cell types and their spatial localization across samples applying a deconvolution strategy using previously published single-nuclei RNA-sequencing data. We identified genes enriched in fat patches and cell types such as fibroadipogenic progenitor cells (FAPs) in areas of active pathology. Using expression data of ligand receptor pairs, we highlight cell-cell communications leading to fibrotic and adipogenic lesions. Finally, analysis of gene expression gradients in areas of adjacent muscle and fat, allowed the identification of genes associated with muscle areas committed to become fat.","doi":"10.1002/path.70067","is_pre_analysis":false,"links":[{"link_name":"Github","link_type":"LAB_WEBSITE","link_url":"https://github.com/Qirongmao97/NMDhuman_spatial"}],"name":"Unraveling the spatial landscape of Dystrophinopathies: a transcriptomic approach to Becker and Duchenne muscular dystrophies","published_at":"2026-05-06T17:47:24+00:00","publisher_metadata":{"authors":[{"family":"Heezen","given":"Laura GM"},{"family":"Mao","given":"Qirong"},{"family":"Nicolau","given":"Stefan"},{"family":"Rausell","given":"Claudio Novella"},{"family":"van der Weerd","given":"Julia"},{"family":"Kueckelhaus","given":"Jan"},{"family":"Gokul Nath","given":"Rasya"},{"family":"Diaz\u2010Manera","given":"Jordi"},{"family":"Kan","given":"Hermien E"},{"family":"Niks","given":"Erik H"},{"family":"van Putten","given":"Maaike"},{"family":"Aartsma\u2010Rus","given":"Annemieke"},{"family":"Flanigan","given":"Kevin M"},{"family":"Mahfouz","given":"Ahmed"},{"family":"Spitali","given":"Pietro"}],"is_preprint":false,"journal":"The Journal of Pathology","published_at":1782864000.0,"published_day":1,"published_month":7,"published_year":2026},"revised_at":"2026-06-11T16:55:23+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"f17b9205-f61f-4a0f-a65a-73ba91c50ade","collection_url":"https://cellxgene.cziscience.com/collections/f17b9205-f61f-4a0f-a65a-73ba91c50ade","collection_version_id":"738a96fb-8505-43c4-937f-573458e7bf23","consortia":["CZI Cell Science"],"contact_email":"genevieve.konopka@utsouthwestern.edu","contact_name":"Genevieve Konopka","created_at":"2026-06-10T15:01:30+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"94c41723-b2c4-4b59-a49a-64c9b851903e","dataset_version_id":"50afa1bf-72df-4739-af9d-9637b9baf04f","disease":[{"label":"epilepsy","ontology_term_id":"MONDO:0005027"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"hippocampal formation","ontology_term_id":"UBERON:0002421","tissue_type":"tissue"}]}],"description":"The hippocampus supports many facets of cognition, including learning, memory, and emotional processing. Anatomically, the hippocampus runs along a longitudinal axis, posterior to anterior in primates. The structure, function, and connectivity of the hippocampus vary along this axis. In human hippocampus, longitudinal functional heterogeneity remains an active area of investigation, and structural heterogeneity has not been described. To understand the cellular and molecular diversity along the hippocampal long axis in human brain and define molecular signatures corresponding to functional domains, we performed single-nuclei RNA sequencing on surgically resected human anterior and posterior hippocampus from epilepsy patients, identifying differentially expressed genes at cellular resolution. We further identify axis- and cell-type-specific gene expression signatures that differentially intersect with human genetic signals, identifying cell-type-specific genes in the posterior hippocampus for cognitive function and the anterior hippocampus for mood and affect. 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With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.","doi":"10.1038/s41586-021-03500-8","is_pre_analysis":false,"links":[{"link_name":"Methyl-C sequencing of single cell nuclei: snmC-seq2","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.pjvdkn6"},{"link_name":"Fresh Frozen Mouse Brain Preparation (for Single Nuclei Sequencing)","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.bcbrism6"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-ch1nqb7"}],"name":"An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types","published_at":"2021-03-08T22:32:08+00:00","publisher_metadata":{"authors":[{"family":"Yao","given":"Zizhen"},{"family":"Liu","given":"Hanqing"},{"family":"Xie","given":"Fangming"},{"family":"Fischer","given":"Stephan"},{"family":"Adkins","given":"Ricky S."},{"family":"Aldridge","given":"Andrew I."},{"family":"Ament","given":"Seth A."},{"family":"Bartlett","given":"Anna"},{"family":"Behrens","given":"M. 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Samples include both healthy and COPD-diseased tissues, specifically from the peripheral lung. Fresh tissue suspensions were processed as single cells using 10x Genomics 3' RNA-seq technology.","doi":"10.1165/rcmb.2021-0555OC","is_pre_analysis":false,"links":[{"link_name":"GSE173896","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173896"}],"name":"Anomalous Epithelial Variations and Ectopic Inflammatory Response in Chronic Obstructive Pulmonary Disease","published_at":"2024-11-20T18:22:53+00:00","publisher_metadata":{"authors":[{"family":"Watanabe","given":"Naoaki"},{"family":"Fujita","given":"Yu"},{"family":"Nakayama","given":"Jun"},{"family":"Mori","given":"Yutaro"},{"family":"Kadota","given":"Tsukasa"},{"family":"Hayashi","given":"Yusuke"},{"family":"Shimomura","given":"Iwao"},{"family":"Ohtsuka","given":"Takashi"},{"family":"Okamoto","given":"Koji"},{"family":"Araya","given":"Jun"},{"family":"Kuwano","given":"Kazuyoshi"},{"family":"Yamamoto","given":"Yusuke"}],"is_preprint":false,"journal":"American Journal of Respiratory Cell and Molecular Biology","published_at":1669852800.0,"published_day":1,"published_month":12,"published_year":2022},"revised_at":"2026-06-11T16:55:19+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"1df8c90d-d299-4b2e-a54d-a5a80f36e780","collection_url":"https://cellxgene.cziscience.com/collections/1df8c90d-d299-4b2e-a54d-a5a80f36e780","collection_version_id":"af2bb049-467c-49e6-b278-0914708fab5d","consortia":[],"contact_email":"arul@umich.edu","contact_name":"Arul M. 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Delineating the cells of origin for different RCC subtypes will provide mechanistic insights into their diverse pathobiology. Here, we employed single-cell RNA sequencing (scRNA-seq) to develop benign and malignant renal cell atlases. Using a random forest model trained on this cell atlas, we predicted the putative cell of origin for more than 10 RCC subtypes. scRNA-seq also revealed several attributes of the tumor microenvironment in the most common subtype of kidney cancer, clear cell RCC (ccRCC). We elucidated an active role for tumor epithelia in promoting immune cell infiltration, potentially explaining why ccRCC responds to immune checkpoint inhibitors, despite having a low neoantigen burden. In addition, we characterized an association between high endothelial cell types and lack of response to immunotherapy in ccRCC. Taken together, these single-cell analyses of benign kidney and RCC provide insight into the putative cell of origin for RCC subtypes and highlight the important role of the tumor microenvironment in influencing ccRCC biology and response to therapy.","doi":"10.1073/pnas.2103240118","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/7c599029-7a3c-4b5c-8e79-e72c9a9a65fe"}],"name":"Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response","published_at":"2023-04-26T10:22:39+00:00","publisher_metadata":{"authors":[{"family":"Zhang","given":"Yuping"},{"family":"Narayanan","given":"Sathiya P."},{"family":"Mannan","given":"Rahul"},{"family":"Raskind","given":"Gregory"},{"family":"Wang","given":"Xiaoming"},{"family":"Vats","given":"Pankaj"},{"family":"Su","given":"Fengyun"},{"family":"Hosseini","given":"Noshad"},{"family":"Cao","given":"Xuhong"},{"family":"Kumar-Sinha","given":"Chandan"},{"family":"Ellison","given":"Stephanie J."},{"family":"Giordano","given":"Thomas J."},{"family":"Morgan","given":"Todd M."},{"family":"Pitchiaya","given":"Sethuramasundaram"},{"family":"Alva","given":"Ajjai"},{"family":"Mehra","given":"Rohit"},{"family":"Cieslik","given":"Marcin"},{"family":"Dhanasekaran","given":"Saravana M."},{"family":"Chinnaiyan","given":"Arul M."}],"is_preprint":false,"journal":"Proc. Natl. Acad. Sci. U.S.A.","published_at":1623715200.0,"published_day":15,"published_month":6,"published_year":2021},"revised_at":"2026-06-11T16:55:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"43b45a20-a969-49ac-a8e8-8c84b211bd01","collection_url":"https://cellxgene.cziscience.com/collections/43b45a20-a969-49ac-a8e8-8c84b211bd01","collection_version_id":"e5491f39-6193-4163-b42e-6c5bc3cdb2ec","consortia":[],"contact_email":"vrk25@cam.ac.uk","contact_name":"Vincent Knight-Schrijver","created_at":"2026-06-10T18:07:03+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5500c673-1610-40a0-86d9-64d987ae50e6","dataset_version_id":"85f6cdae-10c2-4c97-8a95-cf03f87ecd2e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"apex of heart","ontology_term_id":"UBERON:0002098","tissue_type":"tissue"},{"label":"basal zone of heart","ontology_term_id":"UBERON:0035213","tissue_type":"tissue"},{"label":"heart left ventricle","ontology_term_id":"UBERON:0002084","tissue_type":"tissue"},{"label":"heart right ventricle","ontology_term_id":"UBERON:0002080","tissue_type":"tissue"},{"label":"interventricular septum","ontology_term_id":"UBERON:0002094","tissue_type":"tissue"},{"label":"left cardiac atrium","ontology_term_id":"UBERON:0002079","tissue_type":"tissue"},{"label":"right cardiac atrium","ontology_term_id":"UBERON:0002078","tissue_type":"tissue"}]}],"description":"Single-cell transcriptomics data from Adult and Foetal hearts were integrated in R Seurat's reciprocal principal component analysis (RPCA) pipeline. This dataset contains single-cell RNA sequencing of dissociated cells from 7 foetal hearts between the ages of 6 and 10 weeks post-conception (8 to 12 weeks gestational age). Six of these were dissected into either base, or apex, and one of these (F5) was from mostly apex, processed by peeling the epicardial layer in an attempt to enrich for epicardial cells. Foetal 10X scRNA-seq data were combined with adult data 10X scRNA-seq + 10X snRNA sequencing from dissociated cells and nuclei taken from multiple regions of adult 6 healthy adult hearts. Adult heart data was accessed from the Heart Cell Atlas (HCA: Heart Cell Atlas | Home; Cells of the adult human heart)","doi":"10.1038/s44161-022-00183-w","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE216019"}],"name":"Integrated adult and foetal heart single-cell RNA sequencing","published_at":"2023-02-01T18:27:04+00:00","publisher_metadata":{"authors":[{"family":"Knight-Schrijver","given":"Vincent R."},{"family":"Davaapil","given":"Hongorzul"},{"family":"Bayraktar","given":"Semih"},{"family":"Ross","given":"Alexander D. 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We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type\u2013specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.","doi":"10.1038/nn.4216","is_pre_analysis":false,"links":[{"link_name":"GSE71585","link_type":"RAW_DATA","link_url":"http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71585"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-71585"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP6"}],"name":"Adult mouse cortical cell taxonomy revealed by single cell transcriptomics","published_at":"2021-03-08T22:28:16+00:00","publisher_metadata":{"authors":[{"family":"Tasic","given":"Bosiljka"},{"family":"Menon","given":"Vilas"},{"family":"Nguyen","given":"Thuc Nghi"},{"family":"Kim","given":"Tae Kyung"},{"family":"Jarsky","given":"Tim"},{"family":"Yao","given":"Zizhen"},{"family":"Levi","given":"Boaz"},{"family":"Gray","given":"Lucas T"},{"family":"Sorensen","given":"Staci A"},{"family":"Dolbeare","given":"Tim"},{"family":"Bertagnolli","given":"Darren"},{"family":"Goldy","given":"Jeff"},{"family":"Shapovalova","given":"Nadiya"},{"family":"Parry","given":"Sheana"},{"family":"Lee","given":"Changkyu"},{"family":"Smith","given":"Kimberly"},{"family":"Bernard","given":"Amy"},{"family":"Madisen","given":"Linda"},{"family":"Sunkin","given":"Susan M"},{"family":"Hawrylycz","given":"Michael"},{"family":"Koch","given":"Christof"},{"family":"Zeng","given":"Hongkui"}],"is_preprint":false,"journal":"Nat Neurosci","published_at":1454284800.0,"published_day":1,"published_month":2,"published_year":2016},"revised_at":"2026-06-11T16:55:21+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"6d7d23d0-237d-4430-9200-92858abba2d8","collection_url":"https://cellxgene.cziscience.com/collections/6d7d23d0-237d-4430-9200-92858abba2d8","collection_version_id":"13be28e8-97a1-4302-b9a2-e5b434636a34","consortia":[],"contact_email":"alexander.tsankov@mssm.edu","contact_name":"Alexander M. 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In this study, we analyzed over 94,000 cells from single-cell RNA sequencing of immunocompetent murine models, including three samples each for EGFR and NF1-driven GBM and four samples for PDGFB-driven GBM, to systematically characterize the relationship between genotype and immunophenotype in GBM.","doi":"10.1093/brain/awaf129","is_pre_analysis":false,"links":[{"link_name":"GSE203154","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE203154"},{"link_name":"GSE274339","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274339"}],"name":"Single-cell census of murine glioblastoma subtypes","published_at":"2025-04-28T22:29:31+00:00","publisher_metadata":{"authors":[{"family":"Soni","given":"Nishant"},{"family":"Rawat","given":"Kavita"},{"family":"Chen","given":"Zhihong"},{"family":"DiMauro","given":"Angela"},{"family":"Giotti","given":"Bruno"},{"family":"Hambardzumyan","given":"Dolores"},{"family":"Tsankov","given":"Alexander M"}],"is_preprint":false,"journal":"Brain","published_at":1756857600.0,"published_day":3,"published_month":9,"published_year":2025},"revised_at":"2026-06-11T16:55:22+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d36ca85c-3e8b-444c-ba3e-a645040c6185","collection_url":"https://cellxgene.cziscience.com/collections/d36ca85c-3e8b-444c-ba3e-a645040c6185","collection_version_id":"8d4f9d68-ef01-4f95-bb7c-aada3a350f45","consortia":["CZI Cell Science"],"contact_email":"mengjiechen@uchicago.edu","contact_name":"Mengjie Chen","created_at":"2026-06-10T14:00:28+00:00","curator_name":"Erica Marie Rutherford","datasets":[{"assay":[{"label":"10x scATAC-seq","ontology_term_id":"EFO:0030007"}],"dataset_id":"e681c16f-f524-4359-8cd7-718e3c0725dc","dataset_version_id":"7dc986ac-1501-4a2f-8704-76f4983d8382","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"ampulla of fallopian tube","ontology_term_id":"UBERON:0012648","tissue_type":"tissue"},{"label":"fimbria of fallopian tube","ontology_term_id":"UBERON:8410010","tissue_type":"tissue"},{"label":"isthmus of fallopian tube","ontology_term_id":"UBERON:0016632","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"d1207c81-7309-43a7-a5a0-f4283670b62b","dataset_version_id":"2c290f76-a095-4bc9-8eae-21ad226a6c0c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"90d4a63b-5c02-43eb-acde-c49345681601","dataset_version_id":"823e1905-e689-402e-a6d3-b6a0a26b5063","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ampulla of fallopian tube","ontology_term_id":"UBERON:0012648","tissue_type":"tissue"},{"label":"fimbria of fallopian tube","ontology_term_id":"UBERON:8410010","tissue_type":"tissue"},{"label":"isthmus of fallopian tube","ontology_term_id":"UBERON:0016632","tissue_type":"tissue"}]},{"assay":[{"label":"10x scATAC-seq","ontology_term_id":"EFO:0030007"}],"dataset_id":"3a116a52-80db-41f2-a2ad-45db1b86712f","dataset_version_id":"c7749f1b-bc40-4843-aa11-8ab39b30955d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]}],"description":"As part of the Human Cell Atlas initiative, we generated transcriptomic (scRNA-seq; 86,708 cells) and regulatory (scATAC-seq; 59,118 cells) profiles of the normal postmenopausal ovary and fallopian tube (FT) at single-cell resolution. In the FT, 22 cell clusters integrated into 11 cell types, including ciliated and secretory epithelial cells, while the ovary had 17 distinct cell clusters defining 6 major cell types.","doi":"10.1016/j.celrep.2022.111838","is_pre_analysis":false,"links":[{"link_name":"EGAS00001006780","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001006780"}],"name":"A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA and ATAC sequencing","published_at":"2022-10-05T20:08:09+00:00","publisher_metadata":{"authors":[{"family":"Lengyel","given":"Ernst"},{"family":"Li","given":"Yan"},{"family":"Weigert","given":"Melanie"},{"family":"Zhu","given":"Lisha"},{"family":"Eckart","given":"Heather"},{"family":"Javellana","given":"Melissa"},{"family":"Ackroyd","given":"Sarah"},{"family":"Xiao","given":"Jason"},{"family":"Olalekan","given":"Susan"},{"family":"Glass","given":"Dianne"},{"family":"Iyer","given":"Shilpa"},{"family":"Krishnan","given":"Rahul"},{"family":"Bilecz","given":"Agnes Julia"},{"family":"Lastra","given":"Ricardo"},{"family":"Chen","given":"Mengjie"},{"family":"Basu","given":"Anindita"}],"is_preprint":false,"journal":"Cell Reports","published_at":1669852800.0,"published_day":1,"published_month":12,"published_year":2022},"revised_at":"2026-06-11T16:55:32+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"93eebe82-d8c3-41bc-a906-63b5b5f24a9d","collection_url":"https://cellxgene.cziscience.com/collections/93eebe82-d8c3-41bc-a906-63b5b5f24a9d","collection_version_id":"8cf26285-fdb0-4bda-b381-05359e5dc75f","consortia":[],"contact_email":"simon.haas@bih-charite.de","contact_name":"Simon Haas","created_at":"2026-06-10T14:23:27+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"BD Rhapsody Targeted mRNA","ontology_term_id":"EFO:0700004"}],"dataset_id":"d3566d6a-a455-4a15-980f-45eb29114cab","dataset_version_id":"89982e3f-db80-4f08-8a15-acd80f106658","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]},{"assay":[{"label":"BD Rhapsody Targeted mRNA","ontology_term_id":"EFO:0700004"}],"dataset_id":"cd4c96bb-ad66-4e83-ba9e-a7df8790eb12","dataset_version_id":"9388f207-6d35-47a7-bbb5-7fdf7b81dc5b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]},{"assay":[{"label":"BD Rhapsody Whole Transcriptome Analysis","ontology_term_id":"EFO:0700003"}],"dataset_id":"c05fb583-eb2f-4e3a-8e74-f9bd6414e418","dataset_version_id":"a58b36e0-fafe-40d6-a4ca-a659cfe9a1f8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]},{"assay":[{"label":"BD Rhapsody Targeted mRNA","ontology_term_id":"EFO:0700004"}],"dataset_id":"b3a5a10f-b1cb-4e8e-abce-bf345448625b","dataset_version_id":"221e87a6-c54c-4757-8918-36c231ebd382","disease":[{"label":"acute myeloid leukemia","ontology_term_id":"MONDO:0018874"},{"label":"acute promyelocytic leukemia","ontology_term_id":"MONDO:0012883"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bone marrow","ontology_term_id":"UBERON:0002371","tissue_type":"tissue"}]}],"description":"Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.","doi":"10.1038/s41590-021-01059-0","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001005593"},{"link_name":"","link_type":"OTHER","link_url":"https://git.embl.de/triana/nrn"},{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/projects/Supplementary_data_FACS_data_from_Single-cell_proteo-genomic_reference_maps_of_the_human_hematopoietic_system/122716"},{"link_name":"","link_type":"OTHER","link_url":"https://figshare.com/projects/Single-cell_proteo-genomic_reference_maps_of_the_human_hematopoietic_system/94469"},{"link_name":"ABseq App","link_type":"OTHER","link_url":"https://abseqapp.shiny.embl.de/"}],"name":"Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states","published_at":"2022-08-16T21:57:59+00:00","publisher_metadata":{"authors":[{"family":"Triana","given":"Sergio"},{"family":"Vonficht","given":"Dominik"},{"family":"Jopp-Saile","given":"Lea"},{"family":"Raffel","given":"Simon"},{"family":"Lutz","given":"Raphael"},{"family":"Leonce","given":"Daniel"},{"family":"Antes","given":"Magdalena"},{"family":"Hern\u00e1ndez-Malmierca","given":"Pablo"},{"family":"Ordo\u00f1ez-Rueda","given":"Diana"},{"family":"Ramasz","given":"Be\u00e1ta"},{"family":"Boch","given":"Tobias"},{"family":"Jann","given":"Johann-Christoph"},{"family":"Nowak","given":"Daniel"},{"family":"Hofmann","given":"Wolf-Karsten"},{"family":"M\u00fcller-Tidow","given":"Carsten"},{"family":"H\u00fcbschmann","given":"Daniel"},{"family":"Alexandrov","given":"Theodore"},{"family":"Benes","given":"Vladimir"},{"family":"Trumpp","given":"Andreas"},{"family":"Paulsen","given":"Malte"},{"family":"Velten","given":"Lars"},{"family":"Haas","given":"Simon"}],"is_preprint":false,"journal":"Nat Immunol","published_at":1638316800.0,"published_day":1,"published_month":12,"published_year":2021},"revised_at":"2026-06-11T16:55:33+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"51544e44-293b-4c2b-8c26-560678423380","collection_url":"https://cellxgene.cziscience.com/collections/51544e44-293b-4c2b-8c26-560678423380","collection_version_id":"077637e1-7d62-4d27-a644-06d08596a548","consortia":["Human Pancreas Analysis Program (HPAP)"],"contact_email":"vahedi@pennmedicine.upenn.edu","contact_name":"Golnaz Vahedi, Ph.D.","created_at":"2026-06-10T13:33:07+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"37b21763-7f0f-41ae-9001-60bad6e2841d","dataset_version_id":"49ba32ba-16d3-47b5-b16c-e851de62f656","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"type 1 diabetes mellitus","ontology_term_id":"MONDO:0005147"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"islet of Langerhans","ontology_term_id":"UBERON:0000006","tissue_type":"tissue"}]}],"description":"Type 1 diabetes (T1D) is an autoimmune disease of only partially defined etiology in which immune cells destroy insulin-producing beta cells. Using single-cell transcriptomics and an advanced analytical strategy to assess pancreatic islets of T1D, autoantibody-positive, and non-diabetic organ donors, we identified both canonical cell types and rare insulin-expressing cells with a hybrid mixture of endocrine and exocrine gene signatures within all donors. We further found elevated expression of MHC Class II pathway genes in exocrine ductal cells of T1D donors, which we confirmed through CyTOF, in situ imaging mass cytometry, and immunofluorescence analysis. Taken together, our multimodal analyses identify novel cell types and processes that may contribute to T1D immunopathogenesis and provide new cellular and molecular insights into human pancreas function.","doi":"10.1038/s42255-022-00531-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://hpap.pmacs.upenn.edu/"},{"link_name":"Pancreas Atlas dataset page","link_type":"OTHER","link_url":"https://www.pancreatlas.org/datasets/508/explore"},{"link_name":"GSE148073","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148073"}],"name":"Multiomics single-cell analysis of human pancreatic islets reveals novel cellular states in health and type 1 diabetes","published_at":"2021-03-12T22:50:12+00:00","publisher_metadata":{"authors":[{"family":"Fasolino","given":"Maria"},{"family":"Schwartz","given":"Gregory W."},{"family":"Patil","given":"Abhijeet R."},{"family":"Mongia","given":"Aanchal"},{"family":"Golson","given":"Maria L."},{"family":"Wang","given":"Yue J."},{"family":"Morgan","given":"Ashleigh"},{"family":"Liu","given":"Chengyang"},{"family":"Schug","given":"Jonathan"},{"family":"Liu","given":"Jinping"},{"family":"Wu","given":"Minghui"},{"family":"Traum","given":"Daniel"},{"family":"Kondo","given":"Ayano"},{"family":"May","given":"Catherine L."},{"family":"Goldman","given":"Naomi"},{"family":"Wang","given":"Wenliang"},{"family":"Feldman","given":"Michael"},{"family":"Moore","given":"Jason H."},{"family":"Japp","given":"Alberto S."},{"family":"Betts","given":"Michael R."},{"family":"Fasolino","given":"Maria"},{"family":"Schwartz","given":"Gregory W."},{"family":"Patil","given":"Abhijeet R."},{"family":"Mongia","given":"Aanchal"},{"family":"Golson","given":"Maria L."},{"family":"Wang","given":"Yue J."},{"family":"Morgan","given":"Ashleigh"},{"family":"Liu","given":"Chengyang"},{"family":"Schug","given":"Jonathan"},{"family":"Liu","given":"Jinping"},{"family":"Wu","given":"Minghui"},{"family":"Traum","given":"Daniel"},{"family":"Kondo","given":"Ayano"},{"family":"May","given":"Catherine L."},{"family":"Goldman","given":"Naomi"},{"family":"Wang","given":"Wenliang"},{"family":"Feldman","given":"Michael"},{"family":"Moore","given":"Jason H."},{"family":"Japp","given":"Alberto S."},{"family":"Betts","given":"Michael R."},{"family":"Faryabi","given":"Robert B."},{"family":"Naji","given":"Ali"},{"family":"Kaestner","given":"Klaus H."},{"family":"Vahedi","given":"Golnaz"},{"family":"Faryabi","given":"Robert B."},{"family":"Naji","given":"Ali"},{"family":"Kaestner","given":"Klaus H."},{"family":"Vahedi","given":"Golnaz"},{"name":"the HPAP Consortium"}],"is_preprint":false,"journal":"Nat Metab","published_at":1643673600.0,"published_day":1,"published_month":2,"published_year":2022},"revised_at":"2026-06-11T16:55:23+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0dd101f7-9829-44b3-a323-18b113eabeb4","collection_url":"https://cellxgene.cziscience.com/collections/0dd101f7-9829-44b3-a323-18b113eabeb4","collection_version_id":"d7cf1ac6-5574-4dbc-8cf3-3a58364f624f","consortia":["CZI Neurodegeneration Challenge Network"],"contact_email":"simone.mayer@kit.edu","contact_name":"Simone Mayer","created_at":"2026-06-10T13:52:02+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"Parse Evercode Whole Transcriptome v2","ontology_term_id":"EFO:0022601"}],"dataset_id":"d995b85b-69f2-48f4-b6ec-0b7bffd120f5","dataset_version_id":"ba404fa2-44a9-4420-b43c-03f863b12d37","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"organoid"}]}],"description":"Sample multiplexing provides a solution to limited sample throughput in single-cell RNA sequencing (scRNA-seq) experiments. Different strategies for multiplexing are commercially provided by Parse Biosciences combinatorial barcoding (Parse) and 10x Genomics CellPlex combined with microfluidic cell capture (10x). However, the extent to which these two techniques differ when characterizing complex tissues such as regionalized neural organoids and whether data generated from the two techniques can be readily integrated is unknown. Cerebellar organoids are a highly relevant model for understanding evolutionary differences, developmental trajectories, and disease mechanisms of this brain region. However, they have not been extensively characterized through scRNA-seq. Therefore, we compared the two multiplexing techniques, 10x and Parse, using cerebellar organoids derived from three stem cell lines. While both strategies demonstrated technical reproducibility and revealed comparable cellular diversity including the main lineages of cerebellar neurons, we found more stressed cells in 10x than in Parse. Additionally, we observed differences in transcript capture, with Parse covering a higher gene biotype diversity and less mitochondrial and ribosomal protein coding transcripts. In summary, we demonstrate that both techniques provide similar insight into cerebellar organoid biology, but flexibility of experimental design, capture of long transcripts, and the level of cell stress caused by the workflow differ.","doi":"10.1016/j.isci.2026.114780","is_pre_analysis":false,"links":[],"name":"Cerebellar organoid atlas using microfluidics- and combinatorial barcoding-based technologies","published_at":"2026-01-09T19:08:54+00:00","publisher_metadata":{"authors":[{"family":"Sarieva","given":"Kseniia"},{"family":"Kagermeier","given":"Theresa"},{"family":"Lysenkov","given":"Vladislav"},{"family":"Castagnetti","given":"Francesco"},{"family":"Yentuer","given":"Zeynep"},{"family":"Becker","given":"Katharina"},{"family":"Matilainen","given":"Julia"},{"family":"Casadei","given":"Nicolas"},{"family":"Mayer","given":"Simone"}],"is_preprint":false,"journal":"iScience","published_at":1769904000.0,"published_day":1,"published_month":2,"published_year":2026},"revised_at":"2026-06-11T16:55:31+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"fcb3d1c1-03d2-41ac-8229-458e072b7a1c","collection_url":"https://cellxgene.cziscience.com/collections/fcb3d1c1-03d2-41ac-8229-458e072b7a1c","collection_version_id":"78de6edf-6c01-4e0f-b318-aa7a68f0ab10","consortia":["CZI Neurodegeneration Challenge Network"],"contact_email":"mo2738@cumc.columbia.edu","contact_name":"Marta Olah","created_at":"2026-06-10T20:29:50+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"a1b9c51e-a408-4f7f-bccb-abefe20ae2a5","dataset_version_id":"dddc40f4-4969-4eb6-b5e9-b30f03ddd672","disease":[{"label":"Alzheimer disease","ontology_term_id":"MONDO:0004975"},{"label":"temporal lobe epilepsy","ontology_term_id":"MONDO:0005115"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dorsolateral prefrontal cortex","ontology_term_id":"UBERON:0009834","tissue_type":"tissue"},{"label":"temporal cortex","ontology_term_id":"UBERON:0016538","tissue_type":"tissue"}]}],"description":"This single-cell RNA-seq data set was generated from live microglia isolated from autopsy and surgically resected human brain tissue, as described in Olah et al. (Nature Communications, 2020). The data set contains 16,245 total cells from 17 individuals, of which 16,099 (99%) are putative microglia (clusters 1-9) and the remaining cells are putative lymphocytes, monocytes, and erythrocytes. The autopsy donors all had Mild Cognitive Impairment or a diagnosis of Alzheimer\u2019s Disease, whereas the donors from whom surgical tissue was obtained all had diagnoses of Temporal Lobe Epilepsy.","doi":"10.1038/s41467-020-19737-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://vmenon.shinyapps.io/microglia/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/vilasmenon/Microglia_Olah_et_al_2020"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.synapse.org/#!Synapse:syn21438358"}],"name":"Live Human Microglia Single-cell RNA-seq","published_at":"2021-07-20T18:32:52+00:00","publisher_metadata":{"authors":[{"family":"Olah","given":"Marta"},{"family":"Menon","given":"Vilas"},{"family":"Habib","given":"Naomi"},{"family":"Taga","given":"Mariko F."},{"family":"Ma","given":"Yiyi"},{"family":"Yung","given":"Christina J."},{"family":"Cimpean","given":"Maria"},{"family":"Khairallah","given":"Anthony"},{"family":"Coronas-Samano","given":"Guillermo"},{"family":"Sankowski","given":"Roman"},{"family":"Gr\u00fcn","given":"Dominic"},{"family":"Kroshilina","given":"Alexandra A."},{"family":"Dionne","given":"Danielle"},{"family":"Sarkis","given":"Rani A."},{"family":"Cosgrove","given":"Garth R."},{"family":"Helgager","given":"Jeffrey"},{"family":"Golden","given":"Jeffrey A."},{"family":"Pennell","given":"Page B."},{"family":"Prinz","given":"Marco"},{"family":"Vonsattel","given":"Jean Paul G."},{"family":"Teich","given":"Andrew F."},{"family":"Schneider","given":"Julie A."},{"family":"Bennett","given":"David A."},{"family":"Regev","given":"Aviv"},{"family":"Elyaman","given":"Wassim"},{"family":"Bradshaw","given":"Elizabeth M."},{"family":"De Jager","given":"Philip L."}],"is_preprint":false,"journal":"Nat Commun","published_at":1606780800.0,"published_day":1,"published_month":12,"published_year":2020},"revised_at":"2026-06-11T16:55:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0faa1af6-e504-4b88-a47b-69347e1bace5","collection_url":"https://cellxgene.cziscience.com/collections/0faa1af6-e504-4b88-a47b-69347e1bace5","collection_version_id":"0172791a-e8f5-49f0-98e1-cdea32d24278","consortia":["CZI Neurodegeneration Challenge Network"],"contact_email":"Oezguen.Goekce@med.uni-muenchen.de","contact_name":"G\u00f6kce, \u00d6zg\u00fcn Dr.","created_at":"2026-06-10T14:46:03+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a539c7af-fb65-44b1-8812-000b097eac99","dataset_version_id":"2a06f185-7269-4ef1-b360-9679d650518b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"brain gray matter","ontology_term_id":"UBERON:0003528","tissue_type":"tissue"},{"label":"brain white matter","ontology_term_id":"UBERON:0003544","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"6347cc90-f284-41d8-a131-db4a37bd796f","dataset_version_id":"6ee1a030-ddb9-43e5-82eb-4a327a122b7e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"brain gray matter","ontology_term_id":"UBERON:0003528","tissue_type":"tissue"},{"label":"brain white matter","ontology_term_id":"UBERON:0003544","tissue_type":"tissue"}]}],"description":"A hallmark of nervous system aging is a decline of white matter volume and function, but the underlying mechanisms leading to white matter pathology are unknown. Here, we found age-related alterations of oligodendrocytes with a reduction of total oligodendrocyte density in the aging murine white matter. Using single-cell RNA sequencing, we identify interferon-responsive oligodendrocytes, which localize in proximity of CD8+ T cells in the aging white matter. Absence of functional lymphocytes decreased oligodendrocyte reactivity and rescued oligodendrocyte loss, while T-cell checkpoint inhibition worsened the aging effect. In addition, we identified a subpopulation of immune cell-dependent interferon-responsive microglia in the aging white matter, and co-culture experiments revealed that interferon-\u03b3 activated microglia triggered oligodendrocytes cell death. In summary, we provide evidence that T cells induced interferon-responsive oligodendrocytes and microglia are important modifiers of white matter aging.","doi":"10.1038/s41593-022-01183-6","is_pre_analysis":false,"links":[{"link_name":"GSE202579","link_type":"OTHER","link_url":"https://www-ncbi-nlm-nih-gov.stanford.idm.oclc.org/geo/query/acc.cgi?acc=GSE202579"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ISD-SystemsNeuroscience/Aging_Oligos_Microglia"}],"name":"Single-cell transcriptomics characterization of oligodendrocytes and microglia in white matter aging","published_at":"2022-11-11T19:47:57+00:00","publisher_metadata":{"authors":[{"family":"Kaya","given":"Tu\u011fberk"},{"family":"Mattugini","given":"Nicola"},{"family":"Liu","given":"Lu"},{"family":"Ji","given":"Hao"},{"family":"Cantuti-Castelvetri","given":"Ludovico"},{"family":"Wu","given":"Jianping"},{"family":"Schifferer","given":"Martina"},{"family":"Groh","given":"Janos"},{"family":"Martini","given":"Rudolf"},{"family":"Besson-Girard","given":"Simon"},{"family":"Kaji","given":"Seiji"},{"family":"Liesz","given":"Arthur"},{"family":"Gokce","given":"Ozgun"},{"family":"Simons","given":"Mikael"}],"is_preprint":false,"journal":"Nat Neurosci","published_at":1667260800.0,"published_day":1,"published_month":11,"published_year":2022},"revised_at":"2026-06-11T16:55:34+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"16c1e722-96ae-4bf6-b408-cd7f8918484f","collection_url":"https://cellxgene.cziscience.com/collections/16c1e722-96ae-4bf6-b408-cd7f8918484f","collection_version_id":"ccc264ec-f500-4e61-90ae-cdc511aaa58a","consortia":["European Union\u2019s Horizon 2020","Wellcome HCA Strategic Science Support"],"contact_email":"goncalo.castelo-branco@ki.se","contact_name":"Gon\u00e7alo Castelo-Branco","created_at":"2026-06-10T18:16:02+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"dc30c3ec-46d6-4cd8-8ec1-b544a3d0f503","dataset_version_id":"8bbea7c5-c742-4c27-a597-0f1e1383bb48","disease":[{"label":"multiple sclerosis","ontology_term_id":"MONDO:0005301"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"brain white matter","ontology_term_id":"UBERON:0003544","tissue_type":"tissue"}]}],"description":"This dataset features the CCA alignment clustering of white matter tissue from 4 progressive Multiple sclerosis patients different lesions and 5 non neurological controls.","doi":"10.1038/s41586-019-0903-2","is_pre_analysis":false,"links":[{"link_name":"GSE118257","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118257"},{"link_name":"EGAS00001003412","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001003412"},{"link_name":"","link_type":"OTHER","link_url":"https://ki.se/en/mbb/oligointernode"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/38449aea-70b5-40db-84b3-1e08f32efe34"},{"link_name":"PRJEB39323","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/ena/browser/view/PRJEB39323"}],"name":"Single nuclei RNA- sequencing from the white matter of individuals with progressive MS and non-neurological controls","published_at":"2023-11-22T17:37:10+00:00","publisher_metadata":{"authors":[{"family":"J\u00e4kel","given":"Sarah"},{"family":"Agirre","given":"Eneritz"},{"family":"Mendanha Falc\u00e3o","given":"Ana"},{"family":"van Bruggen","given":"David"},{"family":"Lee","given":"Ka Wai"},{"family":"Knuesel","given":"Irene"},{"family":"Malhotra","given":"Dheeraj"},{"family":"ffrench-Constant","given":"Charles"},{"family":"Williams","given":"Anna"},{"family":"Castelo-Branco","given":"Gon\u00e7alo"}],"is_preprint":false,"journal":"Nature","published_at":1548979200.0,"published_day":1,"published_month":2,"published_year":2019},"revised_at":"2026-06-11T16:55:40+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bae2ee8c-b49c-41d0-9097-960d18a39e20","collection_url":"https://cellxgene.cziscience.com/collections/bae2ee8c-b49c-41d0-9097-960d18a39e20","collection_version_id":"e33ba15d-0aca-41aa-9848-1159483da5e4","consortia":[],"contact_email":"wtk22@cam.ac.uk","contact_name":"Walid Khaled","created_at":"2026-06-10T19:06:29+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"6c6b4c47-096d-4084-97e7-714ee10c556c","dataset_version_id":"e05a1540-f925-412d-919c-8e0116c1b4be","disease":[{"label":"neoplasm","ontology_term_id":"MONDO:0005070"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"mammary gland","ontology_term_id":"UBERON:0001911","tissue_type":"tissue"}]}],"description":"It is unclear how genetic aberrations impact the state of nascent tumour cells and their microenvironment. BRCA1 driven triple negative breast cancer (TNBC) has been shown to arise from luminal progenitors yet little is known about how BRCA1 loss-of-function (LOF) and concomitant mutations affect the luminal progenitor cell state. Here we demonstrate how time-resolved single-cell profiling of genetically engineered mouse models before tumour formation can address this challenge. We found that perturbing Brca1/p53 in luminal progenitors induces aberrant alveolar differentiation pre-malignancy accompanied by pro-tumourigenic changes in the immune compartment. Unlike alveolar differentiation during gestation, this process is cell autonomous and characterised by the dysregulation of transcription factors driving alveologenesis. Based on our data we propose a model where Brca1/p53 LOF inadvertently promotes a differentiation program hardwired in luminal progenitors, highlighting the deterministic role of the cell-of-origin and offering a potential explanation for the tissue specificity of BRCA1 tumours.","doi":"10.1038/s41467-021-21783-3","is_pre_analysis":false,"links":[{"link_name":"E-MTAB-10043","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-10043/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/MarioniLab/Tumorigenesis2018"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://marionilab.cruk.cam.ac.uk/BRCA1Tumourigenesis"}],"name":"Time-resolved single-cell analysis of Brca1 associated mammary tumourigenesis reveals aberrant differentiation of luminal progenitors","published_at":"2025-10-16T17:12:58+00:00","publisher_metadata":{"authors":[{"family":"Bach","given":"Karsten"},{"family":"Pensa","given":"Sara"},{"family":"Zarocsinceva","given":"Marija"},{"family":"Kania","given":"Katarzyna"},{"family":"Stockis","given":"Julie"},{"family":"Pinaud","given":"Silvain"},{"family":"Lazarus","given":"Kyren A."},{"family":"Shehata","given":"Mona"},{"family":"Sim\u00f5es","given":"Bruno M."},{"family":"Greenhalgh","given":"Alice R."},{"family":"Howell","given":"Sacha J."},{"family":"Clarke","given":"Robert B."},{"family":"Caldas","given":"Carlos"},{"family":"Halim","given":"Timotheus Y. F."},{"family":"Marioni","given":"John C."},{"family":"Khaled","given":"Walid T."}],"is_preprint":false,"journal":"Nat Commun","published_at":1615248000.0,"published_day":9,"published_month":3,"published_year":2021},"revised_at":"2026-06-11T16:55:41+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0f7d022a-46c7-4e64-be4c-e34adbb78089","collection_url":"https://cellxgene.cziscience.com/collections/0f7d022a-46c7-4e64-be4c-e34adbb78089","collection_version_id":"057ac6ce-06ce-4065-96db-10f87a7920a1","consortia":["CZI Cell Science"],"contact_email":"ruic20@hs.uci.edu","contact_name":"Rui Chen","created_at":"2026-06-10T19:22:31+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"8ef06ea4-8d0f-4303-a652-7d4604402b1f","dataset_version_id":"30127f02-d0b9-4b56-bf4c-e5b77e4989bd","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell","nucleus"],"tissue":[{"label":"cornea","ontology_term_id":"UBERON:0000964","tissue_type":"tissue"},{"label":"corneal endothelium","ontology_term_id":"UBERON:0001985","tissue_type":"tissue"},{"label":"corneal epithelium","ontology_term_id":"UBERON:0001772","tissue_type":"tissue"},{"label":"corneo-scleral junction","ontology_term_id":"UBERON:0006761","tissue_type":"tissue"},{"label":"ocular surface region","ontology_term_id":"UBERON:0010409","tissue_type":"tissue"},{"label":"sclera","ontology_term_id":"UBERON:0001773","tissue_type":"tissue"},{"label":"substantia propria of cornea","ontology_term_id":"UBERON:0001777","tissue_type":"tissue"},{"label":"tunica fibrosa of eyeball","ontology_term_id":"UBERON:0012430","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"8058d760-09e6-4bdd-86a1-36917ffca3ef","dataset_version_id":"9ddcf89a-1329-46a6-b476-d8d3de1f7051","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cornea","ontology_term_id":"UBERON:0000964","tissue_type":"tissue"},{"label":"corneo-scleral junction","ontology_term_id":"UBERON:0006761","tissue_type":"tissue"},{"label":"sclera","ontology_term_id":"UBERON:0001773","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"61adb974-beea-432e-9b4f-677d9cb22ece","dataset_version_id":"2153e987-eff9-4ad1-b7e5-75a48d39afa4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cornea","ontology_term_id":"UBERON:0000964","tissue_type":"tissue"},{"label":"corneal endothelium","ontology_term_id":"UBERON:0001985","tissue_type":"tissue"},{"label":"corneal epithelium","ontology_term_id":"UBERON:0001772","tissue_type":"tissue"},{"label":"corneo-scleral junction","ontology_term_id":"UBERON:0006761","tissue_type":"tissue"},{"label":"ocular surface region","ontology_term_id":"UBERON:0010409","tissue_type":"tissue"},{"label":"sclera","ontology_term_id":"UBERON:0001773","tissue_type":"tissue"},{"label":"substantia propria of cornea","ontology_term_id":"UBERON:0001777","tissue_type":"tissue"},{"label":"tunica fibrosa of eyeball","ontology_term_id":"UBERON:0012430","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"22875b17-dc4a-4870-8ca7-477a088ab898","dataset_version_id":"ce72c454-9b5e-4043-b2f9-abd8f5e9446b","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"cornea","ontology_term_id":"UBERON:0000964","tissue_type":"tissue"},{"label":"corneal epithelium","ontology_term_id":"UBERON:0001772","tissue_type":"tissue"},{"label":"corneo-scleral junction","ontology_term_id":"UBERON:0006761","tissue_type":"tissue"},{"label":"ocular surface region","ontology_term_id":"UBERON:0010409","tissue_type":"tissue"},{"label":"sclera","ontology_term_id":"UBERON:0001773","tissue_type":"tissue"},{"label":"substantia propria of cornea","ontology_term_id":"UBERON:0001777","tissue_type":"tissue"},{"label":"tunica fibrosa of eyeball","ontology_term_id":"UBERON:0012430","tissue_type":"tissue"}]}],"description":"The cornea, limbus, and sclera form the ocular surface, a critical interface that protects the eye, maintains visual function, and provides structural support. The cornea serves as the primary refractive surface and barrier against external pathogens. The limbus, located at the corneal-scleral junction, houses limbal stem cells essential for the regeneration of the corneal epithelium. The sclera provides structural integrity, protects the eye, and serves as the attachment site for extraocular muscles. Together, these three components play integral roles in sustaining ocular function and homeostasis.\n\nTo capture the major cell types and subclasses of the ocular surface, we generated large-scale datasets using scRNA-seq and snRNA-seq technologies from healthy human donors spanning a wide range of ages, genders, and ethnicities. Additionally, publicly available datasets were integrated to expand the scope of the atlas. In total, the atlas includes over 1 million cells and nuclei from 102 donors. We identified 10 major cell classes and 31 types in the atlas, including rare populations such as limbal progenitor cells, Schlemn\u2019s canel endothelium, and specific immune subtypes. The atlas also captures the full trajectory of epithelial differentiation. To further enhance our understanding of gene regulation, we generated a snATAC-seq atlas, profiling over 362k nuclei from 26 donors, including 8 developmental samples, facilitating the characterization of cell type-specific chromatin accessibility landscapes and regulatory elements.\n\nAll datasets underwent a unified preprocessing pipeline and data integration to ensure consistency and quality. The atlas is publicly accessible through CELLxGENE, enabling interactive exploration of gene expression and regulatory landscapes. As part of the Human Cell Atlas initiative, this comprehensive ocular surface atlas marks a significant advance in understanding ocular tissue physiology and provides a valuable resource for studying ocular surface development, aging, and diseases such as corneal dystrophies, limbal stem cell deficiency, and scleral remodeling.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://celltype.info/project/565"}],"name":"Single cell atlas of the human ocular surface","published_at":"2025-05-05T23:35:59+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:55:42+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"28e9d721-6816-48a2-8d0b-43bf0b0c0ebc","collection_url":"https://cellxgene.cziscience.com/collections/28e9d721-6816-48a2-8d0b-43bf0b0c0ebc","collection_version_id":"a315f12d-9e38-44fb-ab40-23a55da11344","consortia":[],"contact_email":"Tom_Mariani@urmc.rochester.edu","contact_name":"Thomas J. 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From more than 800,000 cells we identified 41 cell subclusters across the epithelial, immune, and stromal compartments. The contribution of these different clusters varied according to the natural history of the tissue. Age, parity, and germline mutations, known to modulate the risk of developing breast cancer, affected the homeostatic cellular state of the breast in different ways. We found that immune cells from BRCA1 or BRCA2 carriers had a distinct gene expression signature indicative of potential immune exhaustion which was validated by immunohistochemistry. This suggests that immune escape mechanisms could manifest in non-cancerous tissues very early during tumour initiation. Additionally, we also present the first integrated human breast cell atlas (iHBCA), containing over 2 million cells from 7 of the largest single cell RNA sequencing studies. Together these atlases provide rich resources that can be used to inform novel approaches for early detection and prevention of breast cancer.","doi":"10.1038/s41588-024-01688-9","is_pre_analysis":false,"links":[{"link_name":"trained CellTypist logistic regression models","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.10044650"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/MarioniLab/hbca"},{"link_name":"E-MTAB-13664","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-13664"}],"name":"Human breast cell atlas","published_at":"2023-04-25T16:54:05+00:00","publisher_metadata":{"authors":[{"family":"Reed","given":"Austin D."},{"family":"Pensa","given":"Sara"},{"family":"Steif","given":"Adi"},{"family":"Stenning","given":"Jack"},{"family":"Kunz","given":"Daniel J."},{"family":"Porter","given":"Linsey J."},{"family":"Hua","given":"Kui"},{"family":"He","given":"Peng"},{"family":"Twigger","given":"Alecia-Jane"},{"family":"Siu","given":"Abigail J. 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This data includes 6 subjects, 2 from each timepoint. This data is related to a Egozi et al., Nature Medicine, 2021. Background-subtracted data was normalized to the sum of UMIs, the smallest non-zero value was added to avoid zeros. 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The ILD lungs included samples from 39 individuals with IPF and 27 with other forms of pulmonary fibrosis, including sarcoidosis (n\u2009=\u20094), connective tissue disease-associated ILD (n\u2009=\u20093), idiopathic nonspecific interstitial pneumonia (n\u2009=\u20093), coal worker\u2019s pneumoconiosis (n\u2009=\u20093), chronic hypersensitivity pneumonitis (n\u2009=\u20092), interstitial pneumonia with autoimmune features (n\u2009=\u20092) and unclassifiable ILD (n\u2009=\u200910). Most (67%) the lung samples were from individuals with self-reported ethnicity of European ancestry; 53 (46%) reported past or present tobacco use.","doi":"10.1038/s41588-024-01702-0","is_pre_analysis":false,"links":[{"link_name":"GSE227136","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227136"},{"link_name":"phs003521","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003521"}],"name":"Single-cell RNA-seq analysis of Interstitial Lung Disease (ILD) subtypes","published_at":"2025-10-02T15:48:00+00:00","publisher_metadata":{"authors":[{"family":"Natri","given":"Heini M."},{"family":"Del Azodi","given":"Christina B."},{"family":"Peter","given":"Lance"},{"family":"Taylor","given":"Chase J."},{"family":"Chugh","given":"Sagrika"},{"family":"Kendle","given":"Robert"},{"family":"Chung","given":"Mei-i"},{"family":"Flaherty","given":"David K."},{"family":"Matlock","given":"Brittany K."},{"family":"Calvi","given":"Carla L."},{"family":"Blackwell","given":"Timothy S."},{"family":"Ware","given":"Lorraine B."},{"family":"Bacchetta","given":"Matthew"},{"family":"Walia","given":"Rajat"},{"family":"Shaver","given":"Ciara M."},{"family":"Kropski","given":"Jonathan A."},{"family":"McCarthy","given":"Davis J."},{"family":"Banovich","given":"Nicholas E."}],"is_preprint":false,"journal":"Nat Genet","published_at":1711929600.0,"published_day":1,"published_month":4,"published_year":2024},"revised_at":"2026-06-11T16:55:59+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a26f9885-1b18-410c-a8c2-955ec5bb2efc","collection_url":"https://cellxgene.cziscience.com/collections/a26f9885-1b18-410c-a8c2-955ec5bb2efc","collection_version_id":"a09c42cf-8e1c-419e-b84d-3440f56def8f","consortia":[],"contact_email":"a.senabouth@garvan.org.au","contact_name":"Anne Senabouth","created_at":"2026-06-10T02:04:47+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a41fb1c7-87d1-4840-a375-a1a6b3ab6737","dataset_version_id":"577b178e-0999-4b6e-bd87-d37081c913aa","disease":[{"label":"age-related macular degeneration","ontology_term_id":"MONDO:0005150"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"retinal pigment epithelial cell","ontology_term_id":"CL:0002586","tissue_type":"primary cell culture"}]}],"description":"Single cell RNA-seq of hIPSC-derived Retinal Pigmented Epithelium (RPE) cells cultured from healthy individuals and those with age-related macular degeneration - 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Striatal dysfunction is linked to psychiatric disorders, including opioid use disorder (OUD). Striatal subregions are divided based on neuroanatomy, each with unique roles in OUD. In OUD, the dorsal striatum is involved in altered reward processing, formation of habits, and development of negative affect during withdrawal. Using single nuclei RNA-sequencing, we identified both canonical (e.g., dopamine receptor subtype) and less abundant cell populations (e.g., interneurons) in human dorsal striatum. Pathways related to neurodegeneration, interferon response, and DNA damage were significantly enriched in striatal neurons of individuals with OUD. DNA damage markers were also elevated in striatal neurons of opioid-exposed rhesus macaques. Sex-specific molecular differences in glial cell subtypes associated with chronic stress were found in OUD, particularly female individuals. Together, we describe different cell types in human dorsal striatum and identify cell type-specific alterations in OUD.","doi":"10.1038/s41467-024-45165-7","is_pre_analysis":false,"links":[{"link_name":"GSE233279","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE233279"}],"name":"Transcriptional responses of the human dorsal striatum in opioid use disorder implicates cell type-specifc programs","published_at":"2024-03-02T01:11:00+00:00","publisher_metadata":{"authors":[{"family":"Phan","given":"BaDoi N."},{"family":"Ray","given":"Madelyn H."},{"family":"Xue","given":"Xiangning"},{"family":"Fu","given":"Chen"},{"family":"Fenster","given":"Robert J."},{"family":"Kohut","given":"Stephen J."},{"family":"Bergman","given":"Jack"},{"family":"Haber","given":"Suzanne N."},{"family":"McCullough","given":"Kenneth M."},{"family":"Fish","given":"Madeline K."},{"family":"Glausier","given":"Jill 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Targeting these cells requires a clearer understanding of their injury responses and capacity for repair. Here, we use single nucleus RNA sequencing to profile how each cell type in the lumbar spinal cord changes after a thoracic injury in mice. We present an atlas of these dynamic responses across dozens of cell types in the acute, subacute, and chronically injured spinal cord. Using this resource, we find rare spinal neurons that express a signature of regeneration in response to injury, including a major population that represent spinocerebellar projection neurons. We characterize these cells anatomically and observed axonal sparing, outgrowth, and remodeling in the spinal cord and cerebellum. Together, this work provides a key resource for studying cellular responses to injury and uncovers the spontaneous plasticity of spinocerebellar neurons, uncovering a potential candidate for targeted therapy.","doi":"10.1038/s41467-022-33184-1","is_pre_analysis":false,"links":[{"link_name":"GSE172167","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE172167"}],"name":"Single cell atlas of spinal cord injury in mice reveals a pro-regenerative signature in spinocerebellar neurons.","published_at":"2026-01-06T20:41:10+00:00","publisher_metadata":{"authors":[{"family":"Matson","given":"Kaya J. 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Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, M\u00fcller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult M\u00fcller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.","doi":"10.15252/embj.2018100811","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=adult-retina"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/8185730f-4113-40d3-9cc3-929271784c2b"},{"link_name":"E-MTAB-7316","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-7316"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-MTAB-7316"}],"name":"A single-cell transcriptome atlas of the adult human retina","published_at":"2022-04-26T09:42:03+00:00","publisher_metadata":{"authors":[{"family":"Lukowski","given":"Samuel W"},{"family":"Lo","given":"Camden Y"},{"family":"Sharov","given":"Alexei 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However, little is known about the evolution of the cellular programs underlying cerebellum development in mammals. In this study, we generated single-nucleus RNA-sequencing data for ~400,000 cells to trace cerebellum development from early neurogenesis to adulthood in human, mouse, and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell type generation, except for Purkinje cells, where we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell state markers, and gene expression trajectories across neuronal differentiation show that cerebellar cell type-defining programs have been preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species, or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell type level. Altogether, our study unveils shared and lineage-specific programs governing the development of cerebellar cells, and expands our understanding of mammalian brain evolution.","doi":"10.1038/s41586-023-06884-x","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://home.kaessmannlab.org/index"},{"link_name":"heiDATA repository","link_type":"OTHER","link_url":"https://doi.org/10.11588/data/QDOC4E"},{"link_name":"","link_type":"OTHER","link_url":"https://apps.kaessmannlab.org/sc-cerebellum-transcriptome/"},{"link_name":"","link_type":"OTHER","link_url":"https://gitlab.com/kleiss/mammalian-cerebellum"}],"name":"Cellular development and evolution of the mammalian cerebellum","published_at":"2023-11-30T19:06:08+00:00","publisher_metadata":{"authors":[{"family":"Sepp","given":"Mari"},{"family":"Leiss","given":"Kevin"},{"family":"Murat","given":"Florent"},{"family":"Okonechnikov","given":"Konstantin"},{"family":"Joshi","given":"Piyush"},{"family":"Leushkin","given":"Evgeny"},{"family":"Sp\u00e4nig","given":"Lisa"},{"family":"Mbengue","given":"Noe"},{"family":"Schneider","given":"C\u00e9line"},{"family":"Schmidt","given":"Julia"},{"family":"Trost","given":"Nils"},{"family":"Schauer","given":"Maria"},{"family":"Khaitovich","given":"Philipp"},{"family":"Lisgo","given":"Steven"},{"family":"Palkovits","given":"Mikl\u00f3s"},{"family":"Giere","given":"Peter"},{"family":"Kutscher","given":"Lena M."},{"family":"Anders","given":"Simon"},{"family":"Cardoso-Moreira","given":"Margarida"},{"family":"Sarropoulos","given":"Ioannis"},{"family":"Pfister","given":"Stefan M."},{"family":"Kaessmann","given":"Henrik"}],"is_preprint":false,"journal":"Nature","published_at":1701216000.0,"published_day":29,"published_month":11,"published_year":2023},"revised_at":"2026-06-11T16:52:32+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"bd3f7d45-43a0-4944-8327-62d6c89e2ae1","collection_url":"https://cellxgene.cziscience.com/collections/bd3f7d45-43a0-4944-8327-62d6c89e2ae1","collection_version_id":"5d56d43c-a6c7-45fc-9300-c8021b0b4a2f","consortia":["Human Cell Atlas (HCA)"],"contact_email":"anunya.opa@mahidol.edu","contact_name":"Anunya Opasawatchai","created_at":"2026-06-10T04:48:54+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"bdd109f1-ca27-45dc-bb9f-473008449428","dataset_version_id":"c184cf5a-2c44-4908-96d9-165dd5e07f07","disease":[{"label":"enamel caries","ontology_term_id":"MONDO:0002233"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"pulpitis","ontology_term_id":"MONDO:0006937"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dental pulp","ontology_term_id":"UBERON:0001754","tissue_type":"tissue"}]}],"description":"A comprehensive understanding of dental pulp cellular compositions and their molecular responses to infection are crucial for the advancement of regenerative dentistry. Here, we presented a pilot study of single-cell transcriptomic profiles of 6,810 pulpal cells isolated from a sound human maxillary third molar and three carious teeth with enamel and deep dental caries. We observed altered immune cell compositions of the dental pulp in deep, but not enamel ones. Differential expression analysis revealed up-regulation of several pro-inflammatory, anti-inflammatory, and mineralization-related genes in the immune and stromal cells of the deep dental caries. Making use of an algorithm for predicting cell-to-cell interactions from single-cell transcriptomic profiles, we showed an increase in cell-cell interactions between B cells, plasma cells and macrophages, and other cell types in deep dental caries, including those between TIMP1 (odontoblasts)\u2014CD63 (myeloid cells), and CCL2 (macrophages)\u2014ACKR1 (endothelial cells). Collectively, our work highlighted the single-cell level gene regulations and intercellular interactions in the dental pulps in health and disease.","doi":"10.3389/fdmed.2021.806294","is_pre_analysis":false,"links":[{"link_name":"GSE185222","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185222"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/vclabsysbio/scRNAseq_Dentalpulp"}],"name":"Single-Cell Transcriptomic Profiling of Human Dental Pulp in Sound and Carious Teeth: A Pilot Study","published_at":"2024-10-07T23:54:58+00:00","publisher_metadata":{"authors":[{"family":"Opasawatchai","given":"Anunya"},{"family":"Nguantad","given":"Sarintip"},{"family":"Sriwilai","given":"Benjamaporn"},{"family":"Matangkasombut","given":"Ponpan"},{"family":"Matangkasombut","given":"Oranart"},{"family":"Srisatjaluk","given":"Ratchapin"},{"family":"Charoensawan","given":"Varodom"}],"is_preprint":false,"journal":"Front. Dent. 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The metadata field `cell_type` corresponds to a manual mapping of the original author annotations (metadata field `cell_type_original`) to the Cell Ontology. For the harmonised cell type, region, and neurotransmitter-transporter annotations, please refer to the metadata fields starting with `annot_` in the Author Categories.      2. For the HNOCA extended, you can find the harmonised cell type annotation covering all cells (including the extension datasets) in the `annot_level_2_extended` metadata field.      3. The metadata field `tissue` corresponds to the target tissue of the employed organoid differentiation protocol. For example, a cell originating from a sample generated using a cortical differentiation protocol will be annotated as `cerebral cortex`.     4. The data deposited here contains slightly fewer cells than in the data associated with the original publication. This is due to the removal of some cells with identical expression values as required by the CellxGene schema. You can find the full object at the Zenodo Data Source link to the right.          PUBLICATION ABSTRACT: Neural tissues generated from human pluripotent stem cells in vitro (known as neural organoids) are becoming useful tools to study human brain development, evolution and disease. The characterization of neural organoids using single-cell genomic methods has revealed a large diversity of neural cell types with molecular signatures similar to those observed in primary human brain tissue. However, it is unclear which domains of the human nervous system are covered by existing protocols. It is also difficult to quantitatively assess variation between protocols and the specific cell states in organoids as compared to primary counterparts. Single-cell transcriptome data from primary tissue and neural organoids derived with guided or un-guided approaches and under diverse conditions combined with large-scale integrative analyses make it now possible to address these challenges. Recent advances in computational methodology enable the generation of integrated atlases across many data sets. Here, we integrated 36 single-cell transcriptomics data sets spanning 26 protocols into one integrated human neural organoid cell atlas (HNOCA) totaling over 1.7 million cells. We harmonize cell type annotations by incorporating reference data sets from the developing human brain. By mapping to the developing human brain reference, we reveal which primary cell states have been generated in vitro, and which are under-represented. We further compare transcriptomic profiles of neuronal populations in organoids to their counterparts in the developing human brain. To support rapid organoid phenotyping and quantitative assessment of new protocols, we provide a programmatic interface to browse the atlas and query new data sets, and showcase the power of the atlas to annotate new query data sets and evaluate new organoid protocols. Taken together, the HNOCA will be useful to assess the fidelity of organoids, characterize perturbed and diseased states and facilitate protocol development in the future.","doi":"10.1038/s41586-024-08172-8","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://devsystemslab.github.io/HNOCA-tools/"},{"link_name":"Zenodo","link_type":"DATA_SOURCE","link_url":"https://doi.org/10.5281/zenodo.11203684"}],"name":"An integrated transcriptomic cell atlas of human neural organoids","published_at":"2024-11-26T19:17:18+00:00","publisher_metadata":{"authors":[{"family":"He","given":"Zhisong"},{"family":"Dony","given":"Leander"},{"family":"Fleck","given":"Jonas Simon"},{"family":"Sza\u0142ata","given":"Artur"},{"family":"Li","given":"Katelyn X."},{"family":"Sli\u0161kovi\u0107","given":"Irena"},{"family":"Lin","given":"Hsiu-Chuan"},{"family":"Santel","given":"Malgorzata"},{"family":"Atamian","given":"Alexander"},{"family":"Quadrato","given":"Giorgia"},{"family":"Sun","given":"Jieran"},{"family":"Pa\u0219ca","given":"Sergiu P."},{"name":"Human Cell Atlas Organoid Biological Network"},{"family":"Amin","given":"Neal D."},{"family":"Kelley","given":"Kevin W."},{"family":"Bertucci","given":"Taylor"},{"family":"Temple","given":"Sally"},{"family":"Bowles","given":"Kathryn R."},{"family":"Caporale","given":"Nicol\u00f2"},{"family":"Villa","given":"Emanuele"},{"family":"Testa","given":"Giuseppe"},{"family":"Cruceanu","given":"Cristiana"},{"family":"Binder","given":"Elisabeth B."},{"family":"Camp","given":"J. Gray"},{"family":"Theis","given":"Fabian J."},{"family":"Treutlein","given":"Barbara"}],"is_preprint":false,"journal":"Nature","published_at":1732147200.0,"published_day":21,"published_month":11,"published_year":2024},"revised_at":"2026-06-11T16:52:27+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"172c8f6d-2afa-46ae-8c62-ced6b0827853","collection_url":"https://cellxgene.cziscience.com/collections/172c8f6d-2afa-46ae-8c62-ced6b0827853","collection_version_id":"3c19db07-6c99-4f0a-8f5f-34a06b8916dd","consortia":[],"contact_email":"lindsay.mark@mgh.harvard.edu","contact_name":"Mark E. Lindsay","created_at":"2026-06-09T23:26:33+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"82691839-6879-4810-90f3-67e953f328a3","dataset_version_id":"43a7e4b4-3d41-457c-b0f8-78fce2e59e0c","disease":[{"label":"aortic aneurysm","ontology_term_id":"MONDO:0005160"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"ascending aorta","ontology_term_id":"UBERON:0001496","tissue_type":"tissue"}]}],"description":"We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations.","doi":"10.1161/ATVBAHA.122.317953","is_pre_analysis":false,"links":[{"link_name":"SCP1909","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1909"},{"link_name":"GSE207784","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE207784"}],"name":"Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta","published_at":"2025-11-18T16:56:51+00:00","publisher_metadata":{"authors":[{"family":"Chou","given":"Elizabeth L."},{"family":"Chaffin","given":"Mark"},{"family":"Simonson","given":"Bridget"},{"family":"Pirruccello","given":"James P."},{"family":"Akkad","given":"Amer-Denis"},{"family":"Nekoui","given":"Mahan"},{"family":"Lino Cardenas","given":"Christian Lacks"},{"family":"Bedi","given":"Kenneth C."},{"family":"Nash","given":"Craig"},{"family":"Juric","given":"Dejan"},{"family":"Stone","given":"James R."},{"family":"Isselbacher","given":"Eric M."},{"family":"Margulies","given":"Kenneth B."},{"family":"Klattenhoff","given":"Carla"},{"family":"Ellinor","given":"Patrick T."},{"family":"Lindsay","given":"Mark E."}],"is_preprint":false,"journal":"ATVB","published_at":1667260800.0,"published_day":1,"published_month":11,"published_year":2022},"revised_at":"2026-06-11T16:52:28+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c2879de0-affc-496b-8e2b-f57ed9ec3c34","collection_url":"https://cellxgene.cziscience.com/collections/c2879de0-affc-496b-8e2b-f57ed9ec3c34","collection_version_id":"7b005890-63ba-40e9-93c5-0fe9f1b5c39f","consortia":[],"contact_email":"lizia.branco@kit.edu","contact_name":"L\u00edzia Maria Goncalves Branco","created_at":"2026-06-09T22:34:40+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3a8aec06-3309-4d37-b75d-c59f5f6d55a6","dataset_version_id":"0fff1010-a9fe-4586-b2c7-6359e39d5594","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"neocortex","ontology_term_id":"UBERON:0001950","tissue_type":"organoid"}]}],"description":"This dataset comprises single-cell RNA sequencing data from dorsal forebrain organoids treated with the antiepileptic drug valproic acid (VPA), alongside untreated control organoids, to evaluate the impact of VPA on human brain neurodevelopment. Prenatal exposure to VPA is associated with an increased risk of neurodevelopmental disorders, including autism spectrum disorder. In this organoid model, VPA treatment disrupted the formation of ventricular-like regions and altered processes related to cell-cell and cell-matrix interactions. Transcriptomic analysis revealed reduced expression of genes involved in extracellular matrix secretion and dysregulation of intracellular signaling pathways such as Hippo-YAP/TAZ, which are crucial for sensing and responding to the cellular microenvironment.","doi":null,"is_pre_analysis":false,"links":[],"name":"Single-cell RNA sequencing data of control and VPA-treated dorsal forebrain organoids","published_at":"2026-02-17T17:42:39+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:52:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ad2149fc-19c5-41de-8cfe-44710fbada73","collection_url":"https://cellxgene.cziscience.com/collections/ad2149fc-19c5-41de-8cfe-44710fbada73","collection_version_id":"09f31488-2308-453a-9ac0-7ac7d9ccd2a4","consortia":["BRAIN Initiative","Human Cell Atlas (HCA)"],"contact_email":"li.wang@ucsf.edu","contact_name":"Li Wang","created_at":"2026-06-10T09:17:58+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"aa369999-a034-4ad9-b459-8a93c86ea77b","dataset_version_id":"a4310202-4dc8-4e1b-a96d-d9675f5b14d1","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"Brodmann (1909) area 10","ontology_term_id":"UBERON:0013541","tissue_type":"tissue"},{"label":"Brodmann (1909) area 17","ontology_term_id":"UBERON:8440010","tissue_type":"tissue"},{"label":"Brodmann (1909) area 9","ontology_term_id":"UBERON:0013540","tissue_type":"tissue"},{"label":"forebrain","ontology_term_id":"UBERON:0001890","tissue_type":"tissue"},{"label":"neocortex","ontology_term_id":"UBERON:0001950","tissue_type":"tissue"},{"label":"prefrontal cortex","ontology_term_id":"UBERON:0000451","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"},{"label":"visual cortex","ontology_term_id":"UBERON:0000411","tissue_type":"tissue"}]}],"description":"The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.","doi":"10.1038/s41586-024-08351-7","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-oiif74w"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://cell.ucsf.edu/snMultiome"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/complexdisease/Human_Cortex_Dev_Multiome"}],"name":"Molecular and cellular dynamics of the developing human neocortex at single-cell resolution","published_at":"2024-08-08T22:56:17+00:00","publisher_metadata":{"authors":[{"family":"Wang","given":"Li"},{"family":"Wang","given":"Cheng"},{"family":"Moriano","given":"Juan A."},{"family":"Chen","given":"Songcang"},{"family":"Zuo","given":"Guolong"},{"family":"Cebri\u00e1n-Silla","given":"Arantxa"},{"family":"Zhang","given":"Shaobo"},{"family":"Mukhtar","given":"Tanzila"},{"family":"Wang","given":"Shaohui"},{"family":"Song","given":"Mengyi"},{"family":"de Oliveira","given":"Lilian Gomes"},{"family":"Bi","given":"Qiuli"},{"family":"Augustin","given":"Jonathan J."},{"family":"Ge","given":"Xinxin"},{"family":"Paredes","given":"Mercedes F."},{"family":"Huang","given":"Eric J."},{"family":"Alvarez-Buylla","given":"Arturo"},{"family":"Duan","given":"Xin"},{"family":"Li","given":"Jingjing"},{"family":"Kriegstein","given":"Arnold R."}],"is_preprint":false,"journal":"Nature","published_at":1762387200.0,"published_day":6,"published_month":11,"published_year":2025},"revised_at":"2026-06-11T16:52:30+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0fd39ad7-5d2d-41c2-bda0-c55bde614bdb","collection_url":"https://cellxgene.cziscience.com/collections/0fd39ad7-5d2d-41c2-bda0-c55bde614bdb","collection_version_id":"90b02387-dd58-449d-9d3e-071e51c673f5","consortia":["BRAIN Initiative"],"contact_email":"fkrienen@princeton.edu","contact_name":"Fenna M. 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We used single-nucleus RNA sequencing, analyzing over 2.4 million brain cells sampled from 16 locations in a primate (the common marmoset) to ask whether (1) neurons generally segregate by neurotransmitter status, and (2) neurons expressing the same neurotransmitters share additional molecular features in common, beyond the few genes directly responsible for neurotransmitter synthesis and release. We find the answer to both is \u201cno\u201d: there is a remarkable degree of transcriptional similarity between GABAergic and glutamatergic neurons found in the same brain structure, and there is generally little in common between glutamatergic neurons residing in phylogenetically divergent brain structures. The origin effect is permanent: we find that cell types that cross cephalic boundaries in development retain the transcriptional identities of their birthplaces. GABAergic interneurons, which migrate widely, follow highly specialized and distinct distributions in striatum and neocortex. We use interneuron-restricted AAVs to reveal the morphological diversity of molecularly defined types. Our analyses expose how lineage and functional class sculpt the transcriptional identity and biodistribution of primate neurons.","doi":"10.1126/sciadv.adk3986","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-1je0mn3"},{"link_name":"","link_type":"OTHER","link_url":"https://submit.brainimagelibrary.org/search?grant_number=1-U01-MH114819-01"}],"name":"A marmoset brain cell census reveals influence of developmental origin and functional class on neuronal identity","published_at":"2023-08-11T17:54:10+00:00","publisher_metadata":{"authors":[{"family":"Krienen","given":"Fenna M."},{"family":"Levandowski","given":"Kirsten M."},{"family":"Zaniewski","given":"Heather"},{"family":"del Rosario","given":"Ricardo C.H."},{"family":"Schroeder","given":"Margaret E."},{"family":"Goldman","given":"Melissa"},{"family":"Wienisch","given":"Martin"},{"family":"Lutservitz","given":"Alyssa"},{"family":"Beja-Glasser","given":"Victoria F."},{"family":"Chen","given":"Cindy"},{"family":"Zhang","given":"Qiangge"},{"family":"Chan","given":"Ken Y."},{"family":"Li","given":"Katelyn X."},{"family":"Sharma","given":"Jitendra"},{"family":"McCormack","given":"Dana"},{"family":"Shin","given":"Tay Won"},{"family":"Harrahill","given":"Andrew"},{"family":"Nyase","given":"Eric"},{"family":"Mudhar","given":"Gagandeep"},{"family":"Mauermann","given":"Abigail"},{"family":"Wysoker","given":"Alec"},{"family":"Nemesh","given":"James"},{"family":"Kashin","given":"Seva"},{"family":"Vergara","given":"Josselyn"},{"family":"Chelini","given":"Gabriele"},{"family":"Dimidschstein","given":"Jordane"},{"family":"Berretta","given":"Sabina"},{"family":"Deverman","given":"Benjamin E."},{"family":"Boyden","given":"Ed"},{"family":"McCarroll","given":"Steven A."},{"family":"Feng","given":"Guoping"}],"is_preprint":false,"journal":"Sci. 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Recent landmark studies revealed pervasive differences in renal embryogenesis between mouse and human. The scarcity of detailed gene expression data in humans therefore hampers a thorough understanding of human kidney development and the possible developmental origin of kidney diseases. In this paper, we present a single-cell transcriptomics study of the human fetal kidney. We identified 22 cell types and a host of marker genes. Comparison of samples from different developmental ages revealed continuous gene expression changes in podocytes. To demonstrate the usefulness of our data set, we explored the heterogeneity of the nephrogenic niche, localized podocyte precursors, and confirmed disease-associated marker genes. With close to 18,000 renal cells from five different developmental ages, this study provides a rich resource for the elucidation of human kidney development, easily accessible through an interactive web application.","doi":"10.1371/journal.pbio.3000152","is_pre_analysis":false,"links":[{"link_name":"GSE114530","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114530"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"http://www.semraulab.com/kidney"}],"name":"Single-cell transcriptomics reveals gene expression dynamics of human fetal kidney development","published_at":"2024-10-09T16:43:17+00:00","publisher_metadata":{"authors":[{"family":"Hochane","given":"Maz\u00e8ne"},{"family":"van den Berg","given":"Patrick 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To address this we have created a multi-scale spatial atlas of healthy skin and basal cell carcinoma (BCC), incorporating in vivo optical coherence tomography, single cell RNA sequencing, spatial global transcriptional profiling and in situ sequencing. Computational spatial deconvolution and projection revealed the localisation of distinct cell populations to specific tissue contexts. Although cell populations were conserved between healthy anatomical sites and in BCC, mesenchymal cell populations including fibroblasts and pericytes retained signatures of developmental origin. Spatial profiling and in silico lineage tracing support a hair follicle origin for BCC and demonstrate that cancer-associated fibroblasts are an expansion of a POSTN+ subpopulation associated with hair follicles in healthy skin. RGS5+ pericytes are also expanded in BCC suggesting a role in vascular remodelling. We propose that the identity of mesenchymal cell populations is regulated by signals emanating from adjacent structures and that these signals are repurposed to promote the expansion of skin cancer stroma. The resource we have created is publicly available in an interactive format for the research community.","doi":"10.1073/pnas.2313326120","is_pre_analysis":false,"links":[{"link_name":"Spatial Skin Atlas","link_type":"DATA_SOURCE","link_url":"https://spatial-skin-atlas.cellgeni.sanger.ac.uk"},{"link_name":"scRNAseq (E-MTAB-13085)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-13085"},{"link_name":"Visium (E-MTAB-13084)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-13084"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/e49e556a-da5a-442a-b45c-8691b457623e"}],"name":"Multi-scale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma","published_at":"2024-04-02T16:57:33+00:00","publisher_metadata":{"authors":[{"family":"Ganier","given":"Clarisse"},{"family":"Mazin","given":"Pavel"},{"family":"Herrera-Oropeza","given":"Gabriel"},{"family":"Du-Harpur","given":"Xinyi"},{"family":"Blakeley","given":"Matthew"},{"family":"Gabriel","given":"Jeyrroy"},{"family":"Predeus","given":"Alexander V."},{"family":"Cakir","given":"Batuhan"},{"family":"Prete","given":"Martin"},{"family":"Harun","given":"Nasrat"},{"family":"Darrigrand","given":"Jean-Francois"},{"family":"Haiser","given":"Alexander"},{"family":"Wyles","given":"Saranya"},{"family":"Shaw","given":"Tanya"},{"family":"Teichmann","given":"Sarah A."},{"family":"Haniffa","given":"Muzlifah"},{"family":"Watt","given":"Fiona M."},{"family":"Lynch","given":"Magnus D."}],"is_preprint":false,"journal":"Proc. 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To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56(dim)CD16(hi) NK cells linked positively to circulating interleukin (IL)-15. CD8+ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17\u201323 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19","doi":"10.1016/j.cell.2021.02.018","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.niaid.nih.gov/research/john-tsang-phd"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/niaid/covid19-time-resolved"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161918"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-fatal"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/ae62bb31-55ca-4127-b0fb-b1771a604645"}],"name":"Time-resolved Systems Immunology Reveals a Late Juncture Linked to Fatal COVID-19","published_at":"2021-03-19T16:53:00+00:00","publisher_metadata":{"authors":[{"family":"Liu","given":"Can"},{"family":"Martins","given":"Andrew J."},{"family":"Lau","given":"William W."},{"family":"Rachmaninoff","given":"Nicholas"},{"family":"Chen","given":"Jinguo"},{"family":"Imberti","given":"Luisa"},{"family":"Mostaghimi","given":"Darius"},{"family":"Fink","given":"Danielle L."},{"family":"Burbelo","given":"Peter D."},{"family":"Dobbs","given":"Kerry"},{"family":"Delmonte","given":"Ottavia M."},{"family":"Bansal","given":"Neha"},{"family":"Failla","given":"Laura"},{"family":"Sottini","given":"Alessandra"},{"family":"Quiros-Roldan","given":"Eugenia"},{"family":"Han","given":"Kyu Lee"},{"family":"Sellers","given":"Brian A."},{"family":"Cheung","given":"Foo"},{"family":"Sparks","given":"Rachel"},{"family":"Chun","given":"Tae-Wook"},{"family":"Moir","given":"Susan"},{"family":"Lionakis","given":"Michail S."},{"family":"Abers","given":"Michael S."},{"family":"Apps","given":"Richard"},{"family":"Bosticardo","given":"Marita"},{"family":"Milanez-Almeida","given":"Pedro"},{"family":"Mul\u00e8","given":"Matthew P."},{"family":"Shaw","given":"Elana"},{"family":"Zhang","given":"Yu"},{"family":"Castelli","given":"Francesco"},{"family":"Muiesan","given":"Maria Lorenza"},{"family":"Tomasoni","given":"Gabriele"},{"family":"Scolari","given":"Francesco"},{"family":"Tucci","given":"Alessandra"},{"family":"Rossi","given":"Camillo"},{"family":"Su","given":"Helen C."},{"family":"Kuhns","given":"Douglas B."},{"family":"Cohen","given":"Jeffrey I."},{"family":"Notarangelo","given":"Luigi D."},{"family":"Tsang","given":"John S."}],"is_preprint":false,"journal":"Cell","published_at":1617235200.0,"published_day":1,"published_month":4,"published_year":2021},"revised_at":"2026-06-11T16:52:37+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"37f1f46d-6dfa-482c-9b17-d5850d8536f6","collection_url":"https://cellxgene.cziscience.com/collections/37f1f46d-6dfa-482c-9b17-d5850d8536f6","collection_version_id":"b881485c-c900-4015-90e7-65ce465b450c","consortia":[],"contact_email":"ecker@salk.edu","contact_name":"Joseph R. 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We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing to profile 110,294 nuclei from 45 regions of the mouse cortex, hippocampus, striatum, pallidum, and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements, and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types, and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, an artificial neural network model was constructed that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data allowed prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse brain.","doi":"10.1038/s41586-020-03182-8","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/lhqing/mouse_brain_2020"},{"link_name":"Mouse CEMBA Brain","link_type":"OTHER","link_url":"http://neomorph.salk.edu/mouse_brain.php"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-vmivr5x"},{"link_name":"ALLCools","link_type":"OTHER","link_url":"https://github.com/lhqing/ALLCools"},{"link_name":"Brain Cell Methylation Viewer","link_type":"DATA_SOURCE","link_url":"http://neomorph.salk.edu/omb/"},{"link_name":"YAP","link_type":"OTHER","link_url":"https://hq-1.gitbook.io/mc/"},{"link_name":"GSE132489","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE132489"}],"name":"DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution","published_at":"2021-10-13T19:59:26+00:00","publisher_metadata":{"authors":[{"family":"Liu","given":"Hanqing"},{"family":"Zhou","given":"Jingtian"},{"family":"Tian","given":"Wei"},{"family":"Luo","given":"Chongyuan"},{"family":"Bartlett","given":"Anna"},{"family":"Aldridge","given":"Andrew"},{"family":"Lucero","given":"Jacinta"},{"family":"Osteen","given":"Julia K."},{"family":"Nery","given":"Joseph R."},{"family":"Chen","given":"Huaming"},{"family":"Rivkin","given":"Angeline"},{"family":"Castanon","given":"Rosa G."},{"family":"Clock","given":"Ben"},{"family":"Li","given":"Yang Eric"},{"family":"Hou","given":"Xiaomeng"},{"family":"Poirion","given":"Olivier B."},{"family":"Preissl","given":"Sebastian"},{"family":"Pinto-Duarte","given":"Antonio"},{"family":"O\u2019Connor","given":"Carolyn"},{"family":"Boggeman","given":"Lara"},{"family":"Fitzpatrick","given":"Conor"},{"family":"Nunn","given":"Michael"},{"family":"Mukamel","given":"Eran A."},{"family":"Zhang","given":"Zhuzhu"},{"family":"Callaway","given":"Edward M."},{"family":"Ren","given":"Bing"},{"family":"Dixon","given":"Jesse R."},{"family":"Behrens","given":"M. 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Together, this multi-omic atlas provides an open resource for investigating the evolution of the human brain and identifying novel targets for disease interventions.","doi":"10.1126/sciadv.adh1914","is_pre_analysis":false,"links":[{"link_name":"sci-RNA-seq3","link_type":"PROTOCOL","link_url":"https://doi.org/10.17504/protocols.io.9yih7ue"},{"link_name":"","link_type":"OTHER","link_url":"https://assets.nemoarchive.org/dat-rtmm5q2"},{"link_name":"sci-RNA-seq3 demultiplexing","link_type":"OTHER","link_url":"https://zenodo.org/records/7925943"},{"link_name":"sci-RNA-seq3 preprocessing up to count matrix generation","link_type":"OTHER","link_url":"https://zenodo.org/records/7925933"},{"link_name":"additional analyses","link_type":"OTHER","link_url":"https://zenodo.org/records/7925925"}],"name":"A single-cell transcriptomic atlas spanning the adult rhesus macaque brain","published_at":"2023-09-20T15:24:26+00:00","publisher_metadata":{"authors":[{"family":"Chiou","given":"Kenneth L."},{"family":"Huang","given":"Xingfan"},{"family":"Bohlen","given":"Martin O."},{"family":"Tremblay","given":"S\u00e9bastien"},{"family":"DeCasien","given":"Alex R."},{"family":"O\u2019Day","given":"Diana R."},{"family":"Spurrell","given":"Cailyn H."},{"family":"Gogate","given":"Aishwarya A."},{"family":"Zintel","given":"Trisha M."},{"family":"Andrews","given":"Madeline G."},{"family":"Mart\u00ednez","given":"Melween I."},{"family":"Starita","given":"Lea M."},{"family":"Montague","given":"Michael J."},{"family":"Platt","given":"Michael L."},{"family":"Shendure","given":"Jay"},{"family":"Snyder-Mackler","given":"Noah"},{"name":"Cayo Biobank Research Unit"}],"is_preprint":false,"journal":"Sci. 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Detailed knowledge of the molecular biology of the infection is indispensable for understanding of the viral replication, host responses, and disease progression. We provide gene expression profiles of SARS-CoV and SARS-CoV-2 infections in three human cell lines (H1299, Caco-2 and Calu-3 cells), using bulk and single-cell transcriptomics. Small RNA profiling showed strong expression of the immunity and inflammation-associated microRNA miRNA-155 upon infection with both viruses. SARS-CoV-2 elicited approximately two-fold higher stimulation of the interferon response compared to SARS-CoV in the permissive human epithelial cell line Calu-3, and induction of cytokines such as CXCL10 or IL6. Single cell RNA sequencing data showed that canonical interferon stimulated genes such as IFIT2 or OAS2 were broadly induced, whereas interferon beta (IFNB1) and lambda (IFNL1-4) were expressed only in a subset of infected cells. In addition, temporal resolution of transcriptional responses suggested interferon regulatory factors (IRFs) activities precede that of nuclear factor-\u03baB (NF-\u03baB). Lastly, we identified heat shock proin 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 charperone activity by Tanespimycin/17-N-allylamino-17-demethoxygeldanamycin (17-AAG) resulted in a reduction of viral replication, and of TNF and IL1B mRNA levels. In summary, our study established in vitro cell culture models to study SARS-CoV-2 infection and identified HSP90 protein as potential drug target for therapeutic intervention of SARS-CoV-2 infection.","doi":"10.1016/j.isci.2021.102151","is_pre_analysis":false,"links":[{"link_name":"Landthaler Lab","link_type":"LAB_WEBSITE","link_url":"http://www.mdc-berlin.de/singlecell-SARSCoV2"},{"link_name":"GEO","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148729"},{"link_name":"Supporting files","link_type":"OTHER","link_url":"https://zenodo.org/record/4031204#.YYRtDUbML0p"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-CURD-53"}],"name":"Single-cell gene expression profiling of SARS-CoV-2 infected human cell 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Single cell RNA sequencing analysis defined a multicellular alveolar signaling niche driving alveologenesis which was extensively disrupted by perinatal inflammation, leading to loss of gas exchange surface and alveolar simplification similar to that found in chronic lung disease of newborns. Blockade of IL1b and TNFa ameliorated endotoxin-induced inflammatory lung injury by blunting stromal response to inflammation and modulating innate immune activation in myeloid cells, restoring structural integrity and key signaling networks in the developing alveolus. These data provide new insight into the pathophysiology of developmental lung injury and suggest that modulating inflammation is a promising therapeutic approach to prevent fetal consequences of chorioamnionitis.","doi":"10.1126/scitranslmed.abl8574","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178680"},{"link_name":"Images","link_type":"OTHER","link_url":"https://research.cchmc.org/lungimage/"},{"link_name":"LungMAP ShinyCell","link_type":"OTHER","link_url":"http://bit.ly/rhesuslung_explore"},{"link_name":"LungMAP Portal","link_type":"OTHER","link_url":"http://bit.ly/rhesuslung"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169390"}],"name":"Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates","published_at":"2022-02-23T22:02:47+00:00","publisher_metadata":{"authors":[{"family":"Toth","given":"Andrea"},{"family":"Steinmeyer","given":"Shelby"},{"family":"Kannan","given":"Paranthaman"},{"family":"Gray","given":"Jerilyn"},{"family":"Jackson","given":"Courtney M."},{"family":"Mukherjee","given":"Shibabrata"},{"family":"Demmert","given":"Martin"},{"family":"Sheak","given":"Joshua R."},{"family":"Benson","given":"Daniel"},{"family":"Kitzmiller","given":"Joseph"},{"family":"Wayman","given":"Joseph A."},{"family":"Presicce","given":"Pietro"},{"family":"Cates","given":"Christopher"},{"family":"Rubin","given":"Rhea"},{"family":"Chetal","given":"Kashish"},{"family":"Du","given":"Yina"},{"family":"Miao","given":"Yifei"},{"family":"Gu","given":"Mingxia"},{"family":"Guo","given":"Minzhe"},{"family":"Kalinichenko","given":"Vladimir V."},{"family":"Kallapur","given":"Suhas G."},{"family":"Miraldi","given":"Emily R."},{"family":"Xu","given":"Yan"},{"family":"Swarr","given":"Daniel"},{"family":"Lewkowich","given":"Ian"},{"family":"Salomonis","given":"Nathan"},{"family":"Miller","given":"Lisa"},{"family":"Sucre","given":"Jennifer S."},{"family":"Whitsett","given":"Jeffrey A."},{"family":"Chougnet","given":"Claire A."},{"family":"Jobe","given":"Alan H."},{"family":"Deshmukh","given":"Hitesh"},{"family":"Zacharias","given":"William J."}],"is_preprint":false,"journal":"Sci. 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We performed single-cell RNA sequencing (RNA-seq) on 3,589 cells in a cohort of four patients. We obtained cells from the tumor core as well as surrounding peripheral tissue. Our analysis revealed cellular variation in the tumor's genome and transcriptome. We were also able to identify infiltrating neoplastic cells in regions peripheral to the core lesions. Despite the existence of significant heterogeneity among neoplastic cells, we found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration. Additionally, in investigating the immunological response to the tumors, we found transcriptionally distinct myeloid cell populations residing in the tumor core and the surrounding peritumoral space. 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These data allowed for the creation of models of how T cells with different specific immune functions develop in humans.","doi":"10.1126/science.aay3224","is_pre_analysis":false,"links":[{"link_name":"Zenodo","link_type":"OTHER","link_url":"https://doi.org/10.5281/zenodo.3572422"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/c1810dbc-16d2-45c3-b45e-3e675f88d87b"},{"link_name":"Developmental Cell Atlas","link_type":"LAB_WEBSITE","link_url":"https://developmentcellatlas.ncl.ac.uk"},{"link_name":"ArrayExpress","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8581"},{"link_name":"","link_type":"OTHER","link_url":"http://cells.ucsc.edu/?ds=fetal-thymus"},{"link_name":"E-CURD-79","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-CURD-79"},{"link_name":"E-CURD-80","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-CURD-80"}],"name":"A cell 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Organoids derived from embryonic or induced pluripotent stem cells model development and are guided to specific tissue types via morphogens, whereas organoids derived from tissue-resident fetal or adult stem cells are organ-identity-determined and may model ontogenetic features. However, it has remained difficult to assess the similarity and differences between organoid protocols, and to understand the precision and accuracy of organoid cell states through comparison with primary counterparts. Advances in computational single-cell biology allow the comprehensive integration of datasets with high technical variability. Here, we integrate published single-cell transcriptome datasets from organoids of diverse endoderm-derived tissues including lung, pancreas, intestine, salivary glands, liver, biliary system, stomach, and prostate to establish an initial version of a human endoderm organoid cell atlas (HEOCA). The integration includes nearly one million cells across diverse conditions and data sources. We align and compare cell types and states between organoid models, and harmonize cell type annotations by mapping the atlas to primary tissue counterparts. We focus on intestine and lung, and clarify developmental and adult physiology that can be modeled in vitro. We provide examples of data incorporation from new organoid protocols to expand the atlas, and showcase how comparison to the atlas can illuminate interesting biological features of new datasets. We also show that mapping disease organoid single-cell samples to HEOCA identifies shifts in cell proportion and gene expressions between normal and diseased cells. Taken together, the atlas makes diverse datasets centrally available, and it will be useful to assess organoid fidelity, characterize perturbed and diseased states, streamline protocol development, and will continuously grow in the future.","doi":"10.1038/s41588-025-02182-6","is_pre_analysis":false,"links":[{"link_name":"HEOCA Analysis code","link_type":"OTHER","link_url":"https://github.com/devsystemslab/HEOCA"},{"link_name":"sc2heoca code","link_type":"OTHER","link_url":"https://github.com/devsystemslab/sc2heoca"},{"link_name":"snapseed code","link_type":"OTHER","link_url":"https://github.com/devsystemslab/snapseed"},{"link_name":"wilcoxauc code","link_type":"OTHER","link_url":"https://github.com/bioqxu/wilcoxauc"}],"name":"Integrated human endoderm-derived organoids cell atlas (HEOCA)","published_at":"2024-11-01T20:15:00+00:00","publisher_metadata":{"authors":[{"family":"Xu","given":"Quan"},{"family":"Halle","given":"Lennard"},{"family":"Hediyeh-zadeh","given":"Soroor"},{"family":"Kuijs","given":"Merel"},{"family":"Riedweg","given":"Rya"},{"family":"Kilik","given":"Umut"},{"family":"Recaldin","given":"Timothy"},{"family":"Yu","given":"Qianhui"},{"family":"Rall","given":"Isabell"},{"family":"Frum","given":"Tristan"},{"family":"Adam","given":"Lukas"},{"family":"Parikh","given":"Shrey"},{"family":"Kfuri-Rubens","given":"Raphael"},{"family":"Gander","given":"Manuel"},{"family":"Klein","given":"Dominik"},{"family":"Curion","given":"Fabiola"},{"family":"He","given":"Zhisong"},{"family":"Fleck","given":"Jonas Simon"},{"family":"Oost","given":"Koen"},{"family":"Kahnwald","given":"Maurice"},{"family":"Barbiero","given":"Silvia"},{"family":"Mitrofanova","given":"Olga"},{"family":"Maciag","given":"Grzegorz Jerzy"},{"family":"Jensen","given":"Kim B."},{"family":"Lutolf","given":"Matthias"},{"family":"Liberali","given":"Prisca"},{"family":"Spence","given":"Jason R."},{"family":"Gjorevski","given":"Nikolche"},{"family":"Beumer","given":"Joep"},{"family":"Treutlein","given":"Barbara"},{"family":"Theis","given":"Fabian J."},{"family":"Camp","given":"J. 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These samples were used to assess the presence of Tregs in each patient sample and how that related to the usage of mRNA expression factors (derived using scHPF) in the myeloid, fibroblast, and endothelial lineage. In human samples, lower levels of Tregs were associated with inflammatory and VEGF signaling gene programs that were identified in a mouse model of lung adenocarcinoma after Treg depletion.","doi":"10.1038/s41590-023-01504-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://humantumoratlas.org/explore"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/dpeerlab/Treg_depletion_reproducibility"},{"link_name":"phs002371","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002371"}],"name":"HTAN MSK - Transcriptional connectivity of regulatory T cells in the tumor microenvironment informs novel combination cancer therapy strategies","published_at":"2023-05-01T21:27:56+00:00","publisher_metadata":{"authors":[{"family":"Glasner","given":"Ariella"},{"family":"Rose","given":"Samuel 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However, our understanding of the cellular and molecular mechanisms of muscle ageing is still far from complete. Here, we generate a single-cell and single-nucleus transcriptomic atlas of skeletal muscle ageing from 15 donors across the adult human lifespan, accompanied by myofiber typing using imaging. Our atlas reveals ageing mechanisms acting across different compartments of the muscle, including muscle stem cells (MuSCs), myofibers and the muscle microenvironment. Firstly, we uncover two mechanisms driving MuSC ageing, namely a decrease in ribosome biogenesis and an increase in inflammation. Secondly, we identify a set of nuclei populations explaining the preferential degeneration of the fast-twitch myofibers and suggest two mechanisms acting to compensate for their loss. Importantly, we identify a neuromuscular junction accessory population, which helps myofiber to compensate for aged-related denervation. Thirdly, we reveal multiple microenvironment cell types contributing to the inflammatory milieu of ageing muscle by producing cytokines and chemokines to attract immune cells. Finally, we provide a comparable mouse muscle ageing atlas and further investigate conserved and specific ageing hallmarks across species. In summary, we present a comprehensive human skeletal muscle ageing resource by combining different data modalities, which significantly expands our understanding of muscle biology and ageing.","doi":"10.1038/s43587-024-00613-3","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://www.muscleageingcellatlas.org/"},{"link_name":"E-MTAB-13874","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-13874"}],"name":"Human skeletal muscle ageing atlas","published_at":"2024-06-12T15:30:12+00:00","publisher_metadata":{"authors":[{"family":"Kedlian","given":"Veronika R."},{"family":"Wang","given":"Yaning"},{"family":"Liu","given":"Tianliang"},{"family":"Chen","given":"Xiaoping"},{"family":"Bolt","given":"Liam"},{"family":"Tudor","given":"Catherine"},{"family":"Shen","given":"Zhuojian"},{"family":"Fasouli","given":"Eirini S."},{"family":"Prigmore","given":"Elena"},{"family":"Kleshchevnikov","given":"Vitalii"},{"family":"Pett","given":"Jan Patrick"},{"family":"Li","given":"Tong"},{"family":"Lawrence","given":"John E. 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The progression to ARDS is thought to reflect a combination of increasing viral load, cytopathic effects, translocation of virus into pulmonary tissue, including infection of pulmonary endothelial cells, and inappropriate or insufficient immune responses. Since ARDS is an acute inflammatory injury to the lung, we hypothesize that COVID-19 associated ARDS develops, at least in part, as a direct result of a dysfunctional host immune response that contributes to clinical deterioration in the acute phase of systemic illness, leading to ineffective viral clearance and collateral pulmonary or other tissue damage. Understanding immune signaling that is enhanced or suppressed in patients with worse outcomes has the potential to identify new therapeutic targets for COVID-19 associated ARDS, and knowing the kinetics of potentially pathogenic immune responses will inform the optimal timing of interventions. To address this, the immune and cellular response of infected patients needs to be analyzed comprehensively. Single-cell multi-omics strategies are uniquely poised to do this, given the substantial cellular complexity and the minute clinical samples. Our goals are to rapidly define immune cell states and signaling pathways in COVID-19 that are associated with ARDS severity and to investigate the role of these pathways in ARDS. To achieve this, we enrolled patients in the Emergency Department (ED) in a large, urban, academic hospital from 3/24/2020 to 4/30/2020 in Boston during the peak of the COVID-19 surge, with an institutional IRB-approved waiver of informed consent.","doi":"10.1101/2020.11.20.20227355","is_pre_analysis":false,"links":[{"link_name":"Purification of PBMCs","link_type":"PROTOCOL","link_url":"https://dx.doi.org/10.17504/protocols.io.bjinkkde"},{"link_name":"MGH COVID-19 Effort Blood Processing Protocol for PBMC, Neutrophils and Plasma Isolation","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.bjhnkj5e"},{"link_name":"COVID Blood Processing for scRNAseq","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.bjm6kk9e"},{"link_name":"CITE-seq for PBMCs","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/cite-seq-for-pbmcs-8epv514qjl1b/v1"},{"link_name":"COVID Airway Processing for scRNAseq","link_type":"PROTOCOL","link_url":"http://dx.doi.org/10.17504/protocols.io.bjj8kkrw"},{"link_name":"","link_type":"OTHER","link_url":"https://www.covid19cellatlas.org/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/simslab/cluster_diffex2018"}],"name":"Acute COVID-19 cohort across a range of WHO categories seen at the Department of Emergency Medicine at MGH","published_at":"2022-03-25T15:21:21+00:00","publisher_metadata":{"authors":[{"name":"Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia"},{"family":"Ballestar","given":"Esteban"},{"family":"Farber","given":"Donna L."},{"family":"Glover","given":"Sarah"},{"family":"Horwitz","given":"Bruce"},{"family":"Meyer","given":"Kerstin"},{"family":"Nikoli\u0107","given":"Marko"},{"family":"Ordovas-Montanes","given":"Jose"},{"family":"Sims","given":"Peter"},{"family":"Shalek","given":"Alex"},{"family":"Vandamme","given":"Niels"},{"family":"Vandekerckhove","given":"Linos"},{"family":"Vento-Tormo","given":"Roser"},{"family":"Villani","given":"Alexandra Chloe"}],"is_preprint":true,"journal":"medRxiv","published_at":1606089600.0,"published_day":23,"published_month":11,"published_year":2020},"revised_at":"2026-06-11T16:53:04+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4f30b962-d49b-4624-a233-64f048cf8632","collection_url":"https://cellxgene.cziscience.com/collections/4f30b962-d49b-4624-a233-64f048cf8632","collection_version_id":"4d3187b9-aeaa-4f50-96d6-0eb9de6101d7","consortia":["Human Cell Atlas (HCA)"],"contact_email":"res2003@med.cornell.edu","contact_name":"Renat Shaykhiev","created_at":"2026-06-10T00:27:41+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"b61a921b-7fa3-4b42-b455-aaaf32447920","dataset_version_id":"a8e4f394-d141-4755-9a35-790c734d1dab","disease":[{"label":"chronic obstructive pulmonary disease","ontology_term_id":"MONDO:0005002"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"bronchus","ontology_term_id":"UBERON:0002185","tissue_type":"tissue"},{"label":"segmental bronchus","ontology_term_id":"UBERON:0002184","tissue_type":"tissue"},{"label":"terminal bronchus","ontology_term_id":"UBERON:0002041","tissue_type":"tissue"}]}],"description":"This dataset contains primary single-cell RNA-seq data generated in Dr. Shaykhiev\u2019s laboratory (Weill Cornell Medical College) from human lung tissue obtained from 3 sites (the University of North Carolina Tissue and Cell Culture Procurement Core, the Lung Transplant Program at Columbia University Medical Center, and the Lung Transplant Center at Vanderbilt University Medical Center) from organ donors without history of chronic lung disease (no history of chronic lung disease, NLD) or subjects with chronic obstructive pulmonary disease (COPD). Samples include single-cell suspensions freshly prepared from different anatomic regions dissected from these lung tissue samples, including proximal airways (from NLD samples), pre-terminal distal airways (from NLD and COPD samples) and terminal bronchoalveolar units containing terminal bronchioles and associated adjacent respiratory segments within lobules (from NLD samples), processed as single cells using 10x Genomics 3' RNA-seq technology.","doi":"10.1164/rccm.202207-1384OC","is_pre_analysis":false,"links":[],"name":"A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease","published_at":"2025-01-08T22:11:38+00:00","publisher_metadata":{"authors":[{"family":"Rustam","given":"Samir"},{"family":"Hu","given":"Yang"},{"family":"Mahjour","given":"Seyed Babak"},{"family":"Rendeiro","given":"Andre F."},{"family":"Ravichandran","given":"Hiranmayi"},{"family":"Urso","given":"Andreacarola"},{"family":"D\u2019Ovidio","given":"Frank"},{"family":"Martinez","given":"Fernando J."},{"family":"Altorki","given":"Nasser K."},{"family":"Richmond","given":"Bradley"},{"family":"Polosukhin","given":"Vasiliy"},{"family":"Kropski","given":"Jonathan A."},{"family":"Blackwell","given":"Timothy S."},{"family":"Randell","given":"Scott H."},{"family":"Elemento","given":"Olivier"},{"family":"Shaykhiev","given":"Renat"}],"is_preprint":false,"journal":"American Journal of Respiratory and Critical Care Medicine","published_at":1682899200.0,"published_day":1,"published_month":5,"published_year":2023},"revised_at":"2026-06-11T16:53:11+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ce5b6795-dace-408b-b26b-2ab752c3e20d","collection_url":"https://cellxgene.cziscience.com/collections/ce5b6795-dace-408b-b26b-2ab752c3e20d","collection_version_id":"814be072-1777-444e-9b5c-a1f006a2db00","consortia":[],"contact_email":"Michael.detmar@pharma.ethz.ch","contact_name":"Michael Detmar","created_at":"2026-06-10T06:30:01+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"Smart-seq2","ontology_term_id":"EFO:0008931"}],"dataset_id":"653c66ca-527b-4cb2-a023-a63764c1289a","dataset_version_id":"2897edd1-bd6e-42b6-9c3c-0f42e9248664","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"inguinal lymph node","ontology_term_id":"UBERON:0001542","tissue_type":"tissue"}]}],"description":"Single CD45- CD31+ Podoplanin+ lymphatic endothelial cells were sorted from inguinal lymph nodes of na\u00efve C57Bl/6 and subjected to single-cell RNA sequencing using SmartSeq2.","doi":"10.1371/journal.pbio.3000704","is_pre_analysis":false,"links":[{"link_name":"E-MTAB-8414","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8414"}],"name":"Single-cell mapping of lymphatic endothelial cells in lymph nodes","published_at":"2024-06-04T20:50:26+00:00","publisher_metadata":{"authors":[{"family":"Fujimoto","given":"Noriki"},{"family":"He","given":"Yuliang"},{"family":"D\u2019Addio","given":"Marco"},{"family":"Tacconi","given":"Carlotta"},{"family":"Detmar","given":"Michael"},{"family":"Dieterich","given":"Lothar C."}],"is_preprint":false,"journal":"PLoS Biol","published_at":1586131200.0,"published_day":6,"published_month":4,"published_year":2020},"revised_at":"2026-06-11T16:53:13+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"14dc301f-d4fb-4743-a590-aa88d5f1df1a","collection_url":"https://cellxgene.cziscience.com/collections/14dc301f-d4fb-4743-a590-aa88d5f1df1a","collection_version_id":"b71000d1-32f9-45ae-addb-b0cf481a2414","consortia":[],"contact_email":"mguerrero@carrerasresearch.org","contact_name":"Mercedes Guerrero-Murillo","created_at":"2026-06-09T22:56:02+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v1","ontology_term_id":"EFO:0011025"}],"dataset_id":"460dfe21-0550-4521-92fe-db0f3036d8b0","dataset_version_id":"2aad61a0-31b8-41f5-8b8a-dbd971269f7b","disease":[{"label":"B-cell acute lymphoblastic leukemia","ontology_term_id":"MONDO:0004947"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"T cell","ontology_term_id":"CL:0000084","tissue_type":"primary cell culture"},{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Despite initial high-rates of complete response, <50% of B-cell acute lymphoblastic leukemia (B-ALL) patients treated with CD19-directed chimeric antigen receptor (CAR)-T cells maintain durable remissions. We integrated clonal kinetics and genetic heterogeneity with single-cell-TCR sequencing and single-cell-RNA sequencing, respectively, to explore the cellular dynamics response of both non-transduced (CARneg) and transduced (CARpos) T-cells. CARneg and CARpos T-cells were longitudinally interrogated in the manufactured infusion product (IP) and in peripheral blood at the time of CAR-T cell expansion peak following infusion in five adult B-ALL patients treated with CD19CAR-T products.","doi":"10.1101/2024.01.23.576878","is_pre_analysis":false,"links":[{"link_name":"GSE235760","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE235760"}],"name":"Integrative single-cell multi-omics of CD19-CARpos and CARneg T cells suggest drivers of immunotherapy response in B-ALL","published_at":"2024-08-01T17:15:18+00:00","publisher_metadata":{"authors":[{"family":"Guerrero-Murillo","given":"Mercedes"},{"family":"Rill-Hinarejos","given":"Aina"},{"family":"Trincado","given":"Juan L."},{"family":"Bataller","given":"Alex"},{"family":"Ortiz-Maldonado","given":"Valent\u00edn"},{"family":"Benitez-Ribas","given":"Daniel"},{"family":"Espa\u00f1ol","given":"Marta"},{"family":"Gonz\u00e1lez","given":"Europa Azucena"},{"family":"Martinez-Cibrian","given":"Nuria"},{"family":"Marchese","given":"Dom\u00e9nica"},{"family":"Mart\u00edn-Mart\u00edn","given":"Lourdes"},{"family":"Garcia-Sancho","given":"Alejandro Martin"},{"family":"Heyn","given":"Holger"},{"family":"Juan","given":"Manel"},{"family":"Urbano-Ispiz\u00faa","given":"\u00c1lvaro"},{"family":"Delgado","given":"Julio"},{"family":"Orfao","given":"Alberto"},{"family":"Mereu","given":"Elisabetta"},{"family":"Bueno","given":"Clara"},{"family":"Menendez","given":"Pablo"}],"is_preprint":true,"journal":"bioRxiv","published_at":1706227200.0,"published_day":26,"published_month":1,"published_year":2024},"revised_at":"2026-06-11T16:53:01+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"968834a0-1895-40df-8720-666029b3bbac","collection_url":"https://cellxgene.cziscience.com/collections/968834a0-1895-40df-8720-666029b3bbac","collection_version_id":"ab1e7f9c-2214-4b21-b89c-a4ecfec311ad","consortia":[],"contact_email":"mgreen5@mdanderson.org","contact_name":"Michael R. 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A total of four OFTs were pooled into two independent duplicates (each duplicate consisted of OFTs from two embryos). Single-nuclei RNA-seq of fetal OFTs (week 12) was performed on two fetal samples, one OFT per biological duplicate. Spatial transcriptomics of the fetal (week 12) OFT was also generated. Single-nuclei RNA-seq of adult OFT derivatives (the aortic valves) was performed using three aortic valves, each representing one biological replicate.","doi":"10.7554/eLife.107748.1","is_pre_analysis":false,"links":[{"link_name":"E-MTAB-13456","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-13456"},{"link_name":"E-MTAB-13447","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-13447"},{"link_name":"E-MTAB-13453","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-13453"},{"link_name":"E-MTAB-13461","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-13461"}],"name":"A cell atlas of the developing human outflow tract of the heart and its adult aortic valve derivatives","published_at":"2026-03-03T17:57:57+00:00","publisher_metadata":{"authors":[{"family":"Leshem","given":"Rotem"},{"family":"Baker","given":"Syed Murtuza"},{"family":"Mallen","given":"Joshua"},{"family":"Wang","given":"Lu"},{"family":"Dark","given":"John"},{"family":"Sharrocks","given":"Andrew D"},{"family":"Hanley","given":"Karen Piper"},{"family":"Hanley","given":"Neil A"},{"family":"Rattray","given":"Magnus"},{"family":"Bamforth","given":"Simon D"},{"family":"Bobola","given":"Nicoletta"}],"is_preprint":true,"journal":"eLife","published_at":1757548800.0,"published_day":11,"published_month":9,"published_year":2025},"revised_at":"2026-06-11T16:53:02+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"661a402a-2a5a-4c71-9b05-b346c57bc451","collection_url":"https://cellxgene.cziscience.com/collections/661a402a-2a5a-4c71-9b05-b346c57bc451","collection_version_id":"6c88f568-f847-4acd-aa2a-dc89522f0058","consortia":["European Union\u2019s Horizon 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Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal\u2013mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15+ and TREM2+ fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.","doi":"10.1038/s41586-022-04918-4","is_pre_analysis":false,"links":[{"link_name":"Human scRNA-seq (E-MTAB-10551)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10551"},{"link_name":"Mouse scRNA-seq (E-MTAB-11480)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-11480"},{"link_name":"Reproductive Cell Atlas","link_type":"OTHER","link_url":"http://www.reproductivecellatlas.org/"},{"link_name":"VenTo Lab","link_type":"LAB_WEBSITE","link_url":"https://ventolab.org/"}],"name":"Single-cell roadmap of human gonadal development","published_at":"2023-04-11T16:35:24+00:00","publisher_metadata":{"authors":[{"family":"Garcia-Alonso","given":"Luz"},{"family":"Lorenzi","given":"Valentina"},{"family":"Mazzeo","given":"Cecilia Icoresi"},{"family":"Alves-Lopes","given":"Jo\u00e3o Pedro"},{"family":"Roberts","given":"Kenny"},{"family":"Sancho-Serra","given":"Carmen"},{"family":"Engelbert","given":"Justin"},{"family":"Mare\u010dkov\u00e1","given":"Magda"},{"family":"Gruhn","given":"Wolfram H."},{"family":"Botting","given":"Rachel A."},{"family":"Li","given":"Tong"},{"family":"Crespo","given":"Berta"},{"family":"van Dongen","given":"Stijn"},{"family":"Kiselev","given":"Vladimir Yu"},{"family":"Prigmore","given":"Elena"},{"family":"Herbert","given":"Mary"},{"family":"Moffett","given":"Ashley"},{"family":"Ch\u00e9dotal","given":"Alain"},{"family":"Bayraktar","given":"Omer Ali"},{"family":"Surani","given":"Azim"},{"family":"Haniffa","given":"Muzlifah"},{"family":"Vento-Tormo","given":"Roser"}],"is_preprint":false,"journal":"Nature","published_at":1658361600.0,"published_day":21,"published_month":7,"published_year":2022},"revised_at":"2026-06-11T16:53:04+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a3ffde6c-7ad2-498a-903c-d58e732f7470","collection_url":"https://cellxgene.cziscience.com/collections/a3ffde6c-7ad2-498a-903c-d58e732f7470","collection_version_id":"f36cbb3c-dca9-4ff8-96ca-14e93668a34f","consortia":["CZI Cell Science"],"contact_email":"aviv.regev.sc@gmail.com","contact_name":"Aviv Regev","created_at":"2026-06-10T14:52:34+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"4ed927e9-c099-49af-b8ce-a2652d069333","dataset_version_id":"9130af6d-b035-4c2c-868a-ef9a572270be","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"anterior wall of left ventricle","ontology_term_id":"UBERON:0036288","tissue_type":"tissue"},{"label":"breast","ontology_term_id":"UBERON:0000310","tissue_type":"tissue"},{"label":"esophagus muscularis mucosa","ontology_term_id":"UBERON:0004648","tissue_type":"tissue"},{"label":"gastrocnemius","ontology_term_id":"UBERON:0001388","tissue_type":"tissue"},{"label":"lingula of left lung","ontology_term_id":"UBERON:0008954","tissue_type":"tissue"},{"label":"mucosa","ontology_term_id":"UBERON:0000344","tissue_type":"tissue"},{"label":"prostate gland","ontology_term_id":"UBERON:0002367","tissue_type":"tissue"},{"label":"skin of leg","ontology_term_id":"UBERON:0001511","tissue_type":"tissue"}]}],"description":"Understanding the function of genes and their regulation in tissue homeostasis and disease requires knowing the cellular context in which genes are expressed in tissues across the body. Single cell genomics allows the generation of detailed cellular atlases in human tissues, but most efforts are focused on single tissue types. Here, we establish a framework for profiling multiple tissues across the human body at single-cell resolution using single nucleus RNA-Seq (snRNA-seq), and apply it to 8 diverse, archived, frozen tissue types (three donors per tissue). We apply four snRNA-seq methods to each of 25 samples from 16 donors, generating a cross-tissue atlas of 209,126 nuclei profiles, and benchmark them vs. scRNA-seq of comparable fresh tissues. We use a conditional variational autoencoder (cVAE) to integrate an atlas across tissues, donors, and laboratory methods. We highlight shared and tissue-specific features of tissue-resident immune cells, identifying tissue-restricted and non-restricted resident myeloid populations. These include a cross-tissue conserved dichotomy between LYVE1- and HLA class II-expressing macrophages, and the broad presence of LAM-like macrophages across healthy tissues that is also observed in disease. For rare, monogenic muscle diseases, we identify cell types that likely underlie the neuromuscular, metabolic, and immune components of these diseases, and biological processes involved in their pathology. For common complex diseases and traits analyzed by GWAS, we identify the cell types and gene modules that potentially underlie disease mechanisms. The experimental and analytical frameworks we describe will enable the generation of large-scale studies of how cellular and molecular processes vary across individuals and populations.","doi":"10.1126/science.abl4290","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://www.gtexportal.org/home/datasets"},{"link_name":"dbGaP","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/31887183-a72c-4308-9eac-c6140313f39c"},{"link_name":"Single Cell Portal","link_type":"DATA_SOURCE","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1479/single-nucleus-cross-tissue-molecular-reference-maps"},{"link_name":"UCSC Cell Browser","link_type":"DATA_SOURCE","link_url":"https://cells.ucsc.edu/?ds=cross-tissue-maps"}],"name":"Single-nucleus cross-tissue molecular reference maps to decipher disease gene function","published_at":"2022-06-13T15:09:44+00:00","publisher_metadata":{"authors":[{"family":"Eraslan","given":"G\u00f6kcen"},{"family":"Drokhlyansky","given":"Eugene"},{"family":"Anand","given":"Shankara"},{"family":"Fiskin","given":"Evgenij"},{"family":"Subramanian","given":"Ayshwarya"},{"family":"Slyper","given":"Michal"},{"family":"Wang","given":"Jiali"},{"family":"Van Wittenberghe","given":"Nicholas"},{"family":"Rouhana","given":"John M."},{"family":"Waldman","given":"Julia"},{"family":"Ashenberg","given":"Orr"},{"family":"Lek","given":"Monkol"},{"family":"Dionne","given":"Danielle"},{"family":"Win","given":"Thet Su"},{"family":"Cuoco","given":"Michael S."},{"family":"Kuksenko","given":"Olena"},{"family":"Tsankov","given":"Alexander M."},{"family":"Branton","given":"Philip A."},{"family":"Marshall","given":"Jamie L."},{"family":"Greka","given":"Anna"},{"family":"Getz","given":"Gad"},{"family":"Segr\u00e8","given":"Ayellet V."},{"family":"Aguet","given":"Fran\u00e7ois"},{"family":"Rozenblatt-Rosen","given":"Orit"},{"family":"Ardlie","given":"Kristin G."},{"family":"Regev","given":"Aviv"}],"is_preprint":false,"journal":"Science","published_at":1652400000.0,"published_day":13,"published_month":5,"published_year":2022},"revised_at":"2026-06-11T16:53:06+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d5d0df8f-4eee-49d8-a221-a288f50a1590","collection_url":"https://cellxgene.cziscience.com/collections/d5d0df8f-4eee-49d8-a221-a288f50a1590","collection_version_id":"67790e77-8131-47fe-abd4-384d38660201","consortia":[],"contact_email":"panagiotis.roussos@mssm.edu","contact_name":"Panos Roussos","created_at":"2026-06-10T05:13:29+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"d3cb449b-c2b1-4b50-a7f1-21203535fe61","dataset_version_id":"0270e5e5-ce1d-4165-828e-699210189a92","disease":[{"label":"Parkinson disease","ontology_term_id":"MONDO:0005180"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dorsal motor nucleus of vagus nerve","ontology_term_id":"UBERON:0002870","tissue_type":"tissue"},{"label":"medial globus pallidus","ontology_term_id":"UBERON:0002477","tissue_type":"tissue"},{"label":"prefrontal cortex","ontology_term_id":"UBERON:0000451","tissue_type":"tissue"},{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"},{"label":"primary visual cortex","ontology_term_id":"UBERON:0002436","tissue_type":"tissue"}]}],"description":"Parkinson\u2019s Disease (PD) is a debilitating neurodegenerative disorder, characterized by motor and cognitive impairments, that affects >1% of the population over the age of 60. The pathogenesis of PD is complex and remains largely unknown. Due to the cellular heterogeneity of the human brain and changes in cell type composition with disease progression, this complexity cannot be fully captured with bulk tissue studies. To address this, we generated single-nucleus RNA sequencing and whole-genome sequencing data from 100 postmortem cases and controls, carefully selected to represent the entire spectrum of PD neuropathological severity and diverse clinical symptoms. The single nucleus data were generated from five brain regions, capturing the subcortical and cortical spread of PD pathology. Rigorous preprocessing and quality control were applied to ensure data reliability. Committed to collaborative research and open science, this dataset is available on the AMP PD Knowledge Platform, offering researchers a valuable tool to explore the molecular bases of PD and accelerate advances in understanding and treating the disease.","doi":"10.1038/s41597-024-04117-y","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/DiseaseNeuroGenomics/AMP-PD_SciData"}],"name":"A multi-region single nucleus transcriptomic atlas of Parkinson\u2019s disease","published_at":"2024-12-03T19:13:42+00:00","publisher_metadata":{"authors":[{"family":"N. 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Here, in order to reveal the precise sequence of events during early brain development, we used single-cell RNA sequencing and spatial transcriptomics to uncover cell states and trajectories in human brains at 5 \u2013 14 post-conceptional weeks (p.c.w.). We identified twelve major classes and over 600 distinct cell states, which mapped to precise spatial anatomical domains at 5 p.c.w. We uncovered detailed differentiation trajectories of the human forebrain, and a surprisingly large number of region-specific glioblasts maturing into distinct pre-astrocytes and pre-oligodendrocyte precursor cells (pre-OPCs). Our findings reveal the emergence of cell types during the critical first trimester of human brain development.","doi":"10.1126/science.adf1226","is_pre_analysis":false,"links":[{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/linnarsson-lab/developing-human-brain?tab=readme-ov-file"},{"link_name":"EGAD00001006049","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001006049"}],"name":"Comprehensive cell atlas of the first-trimester developing human brain","published_at":"2024-09-24T17:01:50+00:00","publisher_metadata":{"authors":[{"family":"Braun","given":"Emelie"},{"family":"Danan-Gotthold","given":"Miri"},{"family":"Borm","given":"Lars E."},{"family":"Lee","given":"Ka Wai"},{"family":"Vinsland","given":"Elin"},{"family":"L\u00f6nnerberg","given":"Peter"},{"family":"Hu","given":"Lijuan"},{"family":"Li","given":"Xiaofei"},{"family":"He","given":"Xiaoling"},{"family":"Andrusivov\u00e1","given":"\u017daneta"},{"family":"Lundeberg","given":"Joakim"},{"family":"Barker","given":"Roger A."},{"family":"Arenas","given":"Ernest"},{"family":"Sundstr\u00f6m","given":"Erik"},{"family":"Linnarsson","given":"Sten"}],"is_preprint":false,"journal":"Science","published_at":1697155200.0,"published_day":13,"published_month":10,"published_year":2023},"revised_at":"2026-06-11T16:53:03+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9e4e8f1d-d905-4d4f-b343-84889d0f9ffe","collection_url":"https://cellxgene.cziscience.com/collections/9e4e8f1d-d905-4d4f-b343-84889d0f9ffe","collection_version_id":"f353bb0e-8dcc-40c3-bca6-59cfd984e469","consortia":["CZI Cell Science"],"contact_email":"dfveiga@unicamp.br","contact_name":"Diogo F. 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In this study, we performed multi-omics single-nuclei profiling to map the chromatin accessibility and transcriptome landscapes of FCD type II, generating a comprehensive multimodal single-nuclei dataset comprising 61,525 cells from 11 clinical samples of lesions and controls. Our findings revealed profound chromatin, transcriptomic, and cellular alterations affecting neuronal and glial cells in FCD lesions, including the selective loss of upper-layer excitatory neurons, significant expansion of oligodendrocytes and immature astrocytic populations, and a distinct neuronal subpopulation harboring dysmorphic neurons. Furthermore, we uncovered activated microglia subsets, particularly in FCD IIb cases. This comprehensive study unveils neuronal and glial cell states driving FCD development and epileptogenicity, enhancing our understanding of FCD and offering directions for targeted therapy development.","doi":"10.1016/j.isci.2024.111337","is_pre_analysis":false,"links":[{"link_name":"GSE268807","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE268807"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/9762d70c-9b27-4f57-8cbc-377b9b92ea9b"}],"name":"Multimodal single-cell profiling reveals neuronal vulnerability and pathological cell states in focal cortical dysplasia","published_at":"2024-10-16T16:41:42+00:00","publisher_metadata":{"authors":[{"family":"Galv\u00e3o","given":"Isabella C."},{"family":"Lemoine","given":"Manuela"},{"family":"Messias","given":"Lauana A."},{"family":"Ara\u00fajo","given":"Patr\u00edcia A.O.R.A."},{"family":"Geraldis","given":"Jaqueline 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Damage to the optic nerve can cause vision loss, leading to conditions such as glaucoma, optic neuritis, and optic neuropathy. To advance our understanding of the transcriptomic and epigenetic landscapes, as well as the dynamic cellular processes of the optic nerve, we conducted single-nucleus RNA sequencing (snRNA-seq) and single-nucleus ATAC sequencing (snATAC-seq) on the optic nerve head (ONH) and optic nerve (ON) tissues from over 80 healthy human donor eyes spanning diverse ages, genders, and ethnic backgrounds. By integrating newly generated and previously published snRNA-seq datasets, we constructed a comprehensive ONH and ON cell atlas encompassing transcriptomic profiles of 959,629 nuclei. Our analysis identified 25 distinct cell classes and 86 cell types/states, including diverse populations of astrocytes, oligodendrocytes, oligodendrocyte precursor cells, microglia, and macrophages. Furthermore, snATAC-seq profiling of approximately 1 million nuclei generated high-resolution chromatin accessibility landscapes, enabling the identification of cis-regulatory elements and transcription factors specific to individual cell classes and types. As part of the Human Cell Atlas initiative, our ON atlas serves as a crucial resource for studying optic nerve physiology and deepening our understanding of the cellular and molecular mechanisms underlying optic neuropathies and related diseases.","doi":null,"is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://celltype.info/project/621"}],"name":"Single cell atlas of the human optic nerve","published_at":"2025-05-05T23:36:47+00:00","publisher_metadata":null,"revised_at":"2026-06-11T16:53:06+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"68e7e5b7-4dc9-4609-832e-7656aa6182ba","collection_url":"https://cellxgene.cziscience.com/collections/68e7e5b7-4dc9-4609-832e-7656aa6182ba","collection_version_id":"b697ee90-f2f1-4214-b1bc-87f56be78d24","consortia":["Human Cell Atlas (HCA)"],"contact_email":"enzo.porrello@mcri.edu.au","contact_name":"Enzo R. 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However, many individuals present with isolated upper respiratory symptoms, suggesting potential to constrain viral pathology to the nasopharynx. Which cells SARS-CoV-2 primarily targets and how infection influences the respiratory epithelium remains incompletely understood. We performed scRNA-seq on nasopharyngeal swabs from 58 healthy and COVID-19 participants. During COVID-19, we observe expansion of secretory, loss of ciliated, and epithelial cell repopulation via deuterosomal cell expansion. In mild and moderate COVID-19, epithelial cells express anti-viral/interferon-responsive genes, while cells in severe COVID-19 have muted anti-viral responses despite equivalent viral loads. SARS-CoV-2 RNA+ host-target cells are highly heterogenous, including developing ciliated, interferon-responsive ciliated, AZGP1high goblet, and KRT13+ \u201chillock\u201d-like cells, and we identify genes associated with susceptibility, resistance, or infection response. Our study defines protective and detrimental responses to SARS-CoV-2, the direct viral targets of infection, and suggests that failed nasal epithelial anti-viral immunity may underlie and precede severe COVID-19.","doi":"10.1016/j.cell.2021.07.023","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP1289"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/111d272b-c25a-49ac-9b25-e062b70d66e0"}],"name":"Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19","published_at":"2022-09-20T14:03:25+00:00","publisher_metadata":{"authors":[{"family":"Ziegler","given":"Carly G.K."},{"family":"Miao","given":"Vincent N."},{"family":"Owings","given":"Anna H."},{"family":"Navia","given":"Andrew W."},{"family":"Tang","given":"Ying"},{"family":"Bromley","given":"Joshua 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This study explores the complex interplay of varied cell types in the salivary glands and their role in the pathology of Sj\u00f6gren's Disease.","doi":"10.21203/rs.3.rs-3601404/v2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/pranzatelli/scRNAseqNM2023"},{"link_name":"phs002446","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002446"}],"name":"Single cell and spatial transcriptomics in Sj\u00f6gren\u2019s Disease-affected Human Salivary Glands","published_at":"2024-09-25T16:58:42+00:00","publisher_metadata":{"authors":[{"family":"Pranzatelli","given":"Thomas JF"},{"family":"Perez","given":"Paola"},{"family":"Ku","given":"Anson"},{"family":"Matuck","given":"Bruno Fernandes"},{"family":"Huynh","given":"Khoa"},{"family":"Sakai","given":"Shunsuke"},{"family":"Abed","given":"Mehdi"},{"family":"Jang","given":"Shyh-Ing"},{"family":"Yamada","given":"Eiko"},{"family":"Dominick","given":"Kalie"},{"family":"Ahmed","given":"Zara"},{"family":"Oliver","given":"Amanda"},{"family":"Wasikowski","given":"Rachael"},{"family":"Easter","given":"Quinn T"},{"family":"Baer","given":"Alan N"},{"family":"Pelayo","given":"Eileen"},{"family":"Khavandgar","given":"Zohreh"},{"family":"Gupta","given":"Sarthak"},{"family":"Kleiner","given":"David E"},{"family":"Magone","given":"M Teresa"},{"family":"Lessard","given":"Christopher"},{"family":"Farris","given":"A Darise"},{"family":"Burbelo","given":"Peter D"},{"family":"Martin","given":"Daniel"},{"family":"Morell","given":"Robert"},{"family":"Zheng","given":"Changyu"},{"family":"Rachmaninoff","given":"Nicholas"},{"family":"Maldonado-Ortiz","given":"Jose"},{"family":"Qu","given":"Xufeng"},{"family":"Aure","given":"Marit H"},{"family":"Dezfulian","given":"Mohammad H"},{"family":"Lake","given":"Ross"},{"family":"Teichmann","given":"Sarah"},{"family":"Barber","given":"Daniel L"},{"family":"Tsoi","given":"Lam C"},{"family":"Sowalsky","given":"Adam G"},{"family":"Tyc","given":"Katarzyna M"},{"family":"Liu","given":"Jinze"},{"family":"Gudjonsson","given":"Johann E"},{"family":"Byrd","given":"Kevin M"},{"family":"Johnson","given":"Philip LF"},{"family":"Chiorini","given":"John A"},{"family":"Warner","given":"Blake M"}],"is_preprint":true,"journal":"Research Square","published_at":1720656000.0,"published_day":11,"published_month":7,"published_year":2024},"revised_at":"2026-06-11T16:53:10+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"0e9fd1d3-ef4c-47c6-a2e4-ef4bfadf7c79","collection_url":"https://cellxgene.cziscience.com/collections/0e9fd1d3-ef4c-47c6-a2e4-ef4bfadf7c79","collection_version_id":"64e6ea4f-bb48-4f8a-aa76-f8f095908e50","consortia":[],"contact_email":"m.lattke@imperial.ac.uk","contact_name":"Michael Lattke","created_at":"2026-06-10T16:43:21+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"0df5d172-5888-4cec-9a96-e637636bbfef","dataset_version_id":"f16c25da-15bd-46a4-9a3f-17093f27a2f1","disease":[{"label":"complete trisomy 21","ontology_term_id":"MONDO:0700030"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"0b024b1e-7588-45fc-b794-6fc7192f31ab","dataset_version_id":"54ad14be-a4df-4683-8c69-6346e2a25db9","disease":[{"label":"complete trisomy 21","ontology_term_id":"MONDO:0700030"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"}]}],"description":"Down syndrome (DS), caused by an extra copy of chromosome 21, is the most common genetic form of intellectual disability \naffecting up to 1 in 700 live births. Yet, it remains unclear how the increased dosage of ~200 protein-coding genes on \nchromosome 21 affects brain development, particularly in the cerebral cortex\u2014the area central to higher-level cognitive \nfunctions. Here we generated a single-cell transcriptome and chromatin accessibility atlas from 30 human fetal cortical \nsamples at mid gestation (10-20 weeks after conception), a critical period of cortical development. \n\nThis collection contains the following datasets:\n1) \"Human fetal cortex in Down syndrome, 10X-Multiome (snRNA/ATACseq), complete dataset\" \n   (M04_adata_complete_dataset.h5ad; snRNA-seq dataset including all cell types)\n2) ATAC fragments for complete dataset (M03_ATAC_fragments_concat.tsv.gz)\n3) \"Human fetal cortex in Down syndrome, 10X-Multiome (snRNA/ATACseq), subsetted excitatory lineage\" \n   (M04a_adata_exc_lin.h5ad; snRNA-seq dataset subsetted for excitatory lineage cells; main focus of our analysis)","doi":"10.1038/s41591-026-04211-1","is_pre_analysis":false,"links":[{"link_name":"GSE305153","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305153"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/lattkem1/Down_Syndrome_Multiome"}],"name":"Single-Cell Multiomic Atlas of Human Cortical Development in Down Syndrome","published_at":"2026-04-09T16:53:43+00:00","publisher_metadata":{"authors":[{"family":"Lattke","given":"Michael"},{"family":"Tan","given":"Wee Leng"},{"family":"Sukumaran","given":"Salil Kalarikkal"},{"family":"Utami","given":"Kagistia Hana"},{"family":"Sintes","given":"Marcos"},{"family":"Sakthivel","given":"Srinivasan"},{"family":"Tan","given":"Jonathan"},{"family":"Lim","given":"Auriel"},{"family":"Bansal","given":"Vibhavari Aysha"},{"family":"Rekopoulou","given":"Katerina"},{"family":"Matthews","given":"Nik"},{"family":"Ali\u0107","given":"Ivan"},{"family":"Krsnik","given":"\u017deljka"},{"family":"Ni\u017eeti\u0107","given":"Dean"},{"family":"Levi","given":"Boaz P."},{"family":"De Paola","given":"Vincenzo"}],"is_preprint":false,"journal":"Nat Med","published_at":1772323200.0,"published_day":1,"published_month":3,"published_year":2026},"revised_at":"2026-06-11T16:53:05+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"8f17ac63-aaba-44b5-9b78-60f121da4c2f","collection_url":"https://cellxgene.cziscience.com/collections/8f17ac63-aaba-44b5-9b78-60f121da4c2f","collection_version_id":"1cf34fb8-bac1-4694-86b1-3b90b8b6881d","consortia":["CZI Cell Science"],"contact_email":"chengpa@stanford.edu","contact_name":"Paul Cheng","created_at":"2026-06-10T14:55:24+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"Slide-seqV2","ontology_term_id":"EFO:0030062"}],"dataset_id":"b2005457-dede-4434-a9c3-dbe41fcd542e","dataset_version_id":"c2a7b918-e360-41f4-987a-bb19bb0b9662","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"aorta","ontology_term_id":"UBERON:0000947","tissue_type":"tissue"}]},{"assay":[{"label":"Slide-seqV2","ontology_term_id":"EFO:0030062"}],"dataset_id":"56ce05c9-72f0-47ce-ab6d-f18711cf1be8","dataset_version_id":"07b8dad0-0d94-4028-97d1-1b88a6162768","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["na"],"tissue":[{"label":"right coronary artery","ontology_term_id":"UBERON:0001625","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"43245158-5ae1-4e71-a9a6-67eef49c26bc","dataset_version_id":"473452ed-3b89-466a-9610-14eb36cbd12c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"abdominal aorta","ontology_term_id":"UBERON:0001516","tissue_type":"tissue"},{"label":"arch of aorta","ontology_term_id":"UBERON:0001508","tissue_type":"tissue"},{"label":"ascending aorta","ontology_term_id":"UBERON:0001496","tissue_type":"tissue"},{"label":"bulb of aorta","ontology_term_id":"UBERON:0010172","tissue_type":"tissue"},{"label":"carotid artery segment","ontology_term_id":"UBERON:0005396","tissue_type":"tissue"},{"label":"coronary artery","ontology_term_id":"UBERON:0001621","tissue_type":"tissue"},{"label":"descending aorta","ontology_term_id":"UBERON:0001514","tissue_type":"tissue"},{"label":"iliac artery","ontology_term_id":"UBERON:0005609","tissue_type":"tissue"},{"label":"pulmonary artery","ontology_term_id":"UBERON:0002012","tissue_type":"tissue"},{"label":"right coronary artery","ontology_term_id":"UBERON:0001625","tissue_type":"tissue"}]}],"description":"Human vascular diseases exhibit arterial segment-specific tropisms despite similar genetic and environmental exposures. To understand these differences, we created a human arterial cellular atlas by performing single-cell transcriptomic profiling on multiple arterial sites from healthy donors. This allowed us to identify differences in cellular composition and transcriptomic programs independent of individual variation. We integrated single-cell RNA sequencing data with spatial transcriptomics to identify distinct cell populations and combined this with genetic data to pinpoint potential causal cells and genes linked to vascular phenotypes. Our analysis revealed that fibroblasts and smooth muscle cells are the primary determinants of arterial identity, with significant transcriptomic differences driven by these cells across various vascular beds. Additionally, we discovered that endothelial cells, while mostly similar across vascular beds, include a rare subgroup with unique gene expression patterns. Non-coding RNA profiles also varied significantly by cell type and segment, suggesting an important role in vascular identity and disease. In summary, our study shows that fibroblasts and smooth muscle cells are key to arterial identity, with developmental origins influencing their transcriptomic profiles. Endothelial cells and macrophages show less variation, while non-coding RNA is crucial for vascular-specific gene regulation and disease susceptibility.","doi":"10.1016/j.xgen.2025.101034","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/zhaoshuoxp/czi_rna/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/2245bca0-6563-4e88-ab26-f2b8f60383a7"}],"name":"A Coding and Non-Coding Atlas of the Human Arterial Cell","published_at":"2024-09-12T16:33:00+00:00","publisher_metadata":{"authors":[{"family":"Zhao","given":"Quanyi"},{"family":"Pedroza","given":"Albert"},{"family":"Sharma","given":"Disha"},{"family":"Gu","given":"Wenduo"},{"family":"Dalal","given":"Alex"},{"family":"Weldy","given":"Chad"},{"family":"Jackson","given":"William"},{"family":"Li","given":"Daniel Yuhang"},{"family":"Ryan","given":"Yana"},{"family":"Nguyen","given":"Trieu"},{"family":"Shad","given":"Rohan"},{"family":"Palmisano","given":"Brian T."},{"family":"Monteiro","given":"Jo\u00e3o P."},{"family":"Worssam","given":"Matthew"},{"family":"Berezowitz","given":"Alexa"},{"family":"Iyer","given":"Meghana"},{"family":"Shi","given":"Huitong"},{"family":"Kundu","given":"Ramendra"},{"family":"Limbu","given":"Lasemahang"},{"family":"Kim","given":"Juyong Brian"},{"family":"Kundaje","given":"Anshul"},{"family":"Fischbein","given":"Michael"},{"family":"Wirka","given":"Robert"},{"family":"Quertermous","given":"Thomas"},{"family":"Cheng","given":"Paul"}],"is_preprint":false,"journal":"Cell Genomics","published_at":1764547200.0,"published_day":1,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:53:07+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"222e800b-c9cb-4572-831d-48f8c2ef66b9","collection_url":"https://cellxgene.cziscience.com/collections/222e800b-c9cb-4572-831d-48f8c2ef66b9","collection_version_id":"8bbac8b3-338e-4977-b1a7-6f912418f9bc","consortia":[],"contact_email":"s.m.chuva_de_sousa_lopes@lumc.nl","contact_name":"Susana M. Chuva de Sousa Lopes","created_at":"2026-06-10T04:50:48+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"7178ec0a-b0e2-45b1-beb0-879bb69d81e9","dataset_version_id":"485304df-2065-48a6-8c16-3ff536e21eee","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"mesonephros","ontology_term_id":"UBERON:0000080","tissue_type":"tissue"},{"label":"ovary","ontology_term_id":"UBERON:0000992","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"43dc52cb-92eb-4256-b3a8-5ef220b3d292","dataset_version_id":"ac7034f8-a5d5-4ab7-ac05-06e951f461c8","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"epididymis","ontology_term_id":"UBERON:0001301","tissue_type":"tissue"},{"label":"mesonephros","ontology_term_id":"UBERON:0000080","tissue_type":"tissue"},{"label":"testis","ontology_term_id":"UBERON:0000473","tissue_type":"tissue"}]}],"description":"During human fetal development, sex differentiation occurs not only in the gonads but also in the adjacent developing reproductive tract. However, while the cellular composition of male and female human fetal gonads is well described, that of the adjacent developing reproductive tract remains poorly characterized. Here, we performed single-cell transcriptomics on male and female human fetal gonads together with the adjacent developing reproductive tract from first and second trimesters, highlighting the morphological and molecular changes during sex differentiation. We validated different cell populations of the developing reproductive tract and gonads and compared the molecular signatures between the first and second trimesters, as well as between sexes, to identify conserved and sex-specific features. Together, our study provides insights into human fetal sex-specific gonadogenesis and development of the reproductive tract beyond the gonads.","doi":"10.1016/j.devcel.2024.01.006","is_pre_analysis":false,"links":[{"link_name":"GSE181558","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE181558"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://github.com/chuvalab/embryo_gonads"}],"name":"Characterization of the human fetal gonad and reproductive tract by single-cell transcriptomics","published_at":"2026-05-19T16:06:43+00:00","publisher_metadata":{"authors":[{"family":"Taelman","given":"Jasin"},{"family":"Czukiewska","given":"Sylwia M."},{"family":"Moustakas","given":"Ioannis"},{"family":"Chang","given":"Yolanda W."},{"family":"Hillenius","given":"Sanne"},{"family":"van der Helm","given":"Talia"},{"family":"van der Meeren","given":"Lotte E."},{"family":"Mei","given":"Hailiang"},{"family":"Fan","given":"Xueying"},{"family":"Chuva de Sousa Lopes","given":"Susana M."}],"is_preprint":false,"journal":"Developmental Cell","published_at":1706745600.0,"published_day":1,"published_month":2,"published_year":2024},"revised_at":"2026-06-11T16:53:08+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"73f82ac8-15cc-4fcd-87f8-5683723fce7f","collection_url":"https://cellxgene.cziscience.com/collections/73f82ac8-15cc-4fcd-87f8-5683723fce7f","collection_version_id":"bccaf605-e88a-436b-9286-ae72c9034d98","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"muzlifah.haniffa@sanger.ac.uk","contact_name":"MUZLIFAH HANIFFA","created_at":"2026-06-10T04:53:36+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"f0f0d7c4-3bec-428e-9539-c99d36548d96","dataset_version_id":"f8b5c4f4-7ece-4314-9f49-fc254bbd5c71","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"dermis","ontology_term_id":"UBERON:0002067","tissue_type":"tissue"},{"label":"skin epidermis","ontology_term_id":"UBERON:0001003","tissue_type":"tissue"}]}],"description":"The skin confers biophysical and immunological protection through a complex cellular network established early in embryonic development. We profiled the transcriptomes of more than 500,000 single cells from developing human fetal skin, healthy adult skin, and adult skin with atopic dermatitis and psoriasis. We leveraged these datasets to compare cell states across development, homeostasis, and disease. Our analysis revealed an enrichment of innate immune cells in skin during the first trimester and clonal expansion of disease-associated lymphocytes in atopic dermatitis and psoriasis. We uncovered and validated in situ a reemergence of prenatal vascular endothelial cell and macrophage cellular programs in atopic dermatitis and psoriasis lesional skin. These data illustrate the dynamism of cutaneous immunity and provide opportunities for targeting pathological developmental programs in inflammatory skin diseases.","doi":"10.1126/science.aba6500","is_pre_analysis":false,"links":[{"link_name":"Online web portal","link_type":"DATA_SOURCE","link_url":"https://developmental.cellatlas.io/diseased-skin"},{"link_name":"Raw sequencing data","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8142"},{"link_name":"Data analysis scripts","link_type":"OTHER","link_url":"https://zenodo.org/records/4249674"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/c5f46615-68de-4cf4-bbc2-a0ae10f08243"}],"name":"Developmental cell programs are co-opted in inflammatory skin disease","published_at":"2024-01-01T22:08:26+00:00","publisher_metadata":{"authors":[{"family":"Reynolds","given":"Gary"},{"family":"Vegh","given":"Peter"},{"family":"Fletcher","given":"James"},{"family":"Poyner","given":"Elizabeth F. 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We applied CITE-seq (single-cell RNA and surface protein sequencing) to paired peripheral blood and synovial fluid from treatment-naive patients with juvenile idiopathic arthritis, specifically enriching for innate lymphocytes and dendritic cells (DCs). Integrating these profiles with a comprehensive multi-tissue cohort (Bolton, Mahony et al., 2025, Sci Transl Med, DOI: 10.1126/scitranslmed.adt6050) allowed us to generate a high-resolution cellular atlas of the synovial innate immune landscape. We further identify and define highly activated, XCL1/XCL2-producing synovial natural killer (NK) cell states alongside a restructured DC compartment. These analyses define biological pathways relevant to pathogenic tissue niches, including the robust expansion of XCR1+ cDC1s and their potential to transition into mature regulatory DCs (mregDCs). To serve as a valuable resource to the research community and facilitate open exploration, this collection provides three interactive datasets. The first, the global cellular landscape, encompasses the overarching ecosystem of blood, synovial fluid, and disaggregated synovial tissue populations. The second provides high-resolution subsets of NK cells and helper innate lymphoid cells, while the third isolates high-resolution subsets of cDC1s, cDC2s, plasmacytoid DCs, and mregDCs. Regarding data usage, please cite the appropriate manuscripts based on the datasets analysed. When utilising the innate lymphocyte or DC datasets, cite our primary manuscript. For general analyses of the global cellular landscape, cite both our primary manuscript and Bolton, Mahony et al., 2025. For analyses specifically isolating the synovial tissue data, solely cite Bolton, Mahony et al., 2025.","doi":"10.64898/2026.05.01.716870","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/ollieeknight/paper_nk_cells_in_jia"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://immunologie.charite.de/forschung/ag_romagnani"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://zenodo.org/records/18514472"}],"name":"A single-cell atlas of innate immunity in treatment-naive juvenile idiopathic arthritis","published_at":"2026-05-08T20:57:41+00:00","publisher_metadata":{"authors":[{"family":"Knight","given":"Oliver C."},{"family":"Giordano","given":"Chiara"},{"family":"von Stuckrad","given":"Anne Sae Lim"},{"family":"Winning","given":"Cornelia"},{"family":"Bolton","given":"Chrissy"},{"family":"Mahony","given":"Christopher B."},{"family":"Mashreghi","given":"Mir-Farzin"},{"family":"Croft","given":"Adam 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including photoreceptors, horizontal cells, amacrine, bipolar, and retinal ganglion cells. Each class of neuron can be further classified into subgroups with the abundance varying three orders of magnitude. Therefore, to capture all cell types in the retina and generate a complete single cell reference atlas, it is essential to scale up from currently published single cell profiling studies to improve the sensitivity. In addition, to gain a better understanding of gene regulation at single cell level, it is important to include sufficient scATAC-seq data in the reference. To fill the gap, we performed snRNA-seq and snATAC-seq for the retina from healthy donors. To further increase the size of the dataset, we then collected and incorporated publicly available datasets. All data underwent a unified preprocessing pipeline and data integration. Multiple integration methods were benchmarked by scIB, and scVI was chosen. To harness the power of multiomics, snATAC-seq datasets were also preprocessed, and scGlue was used to generate co-embeddings between snRNA-seq and snATAC-seq cells. To facilitate the public use of references, we employ CELLxGENE and UCSC Cell Browser for visualization. By combining previously published and newly generated datasets, a single cell atlas of the human retina that is composed of 2.5 million single cells from 48 donors has been generated. As a result, over 90 distinct cell types are identified based on the transcriptomics profile with the rarest cell type accounting for about 0.01% of the cell population. In addition, open chromatin profiling has been generated for over 400K nuclei via single nuclei ATAC-seq, allowing systematic characterization of cis-regulatory elements for individual cell type. Integrative analysis reveals intriguing differences in the transcriptome, chromatin landscape, and gene regulatory network among cell class, subgroup, and type. In addition, changes in cell proportion, gene expression and chromatin openness have been observed between different gender and over age. Accessible through interactive browsers, this study represents the most comprehensive reference cell atlas of the human retina to date. As part of the human cell atlas project, this resource lays the foundation for further research in understanding retina biology and diseases.","doi":"10.1038/s41588-025-02454-1","is_pre_analysis":false,"links":[{"link_name":"Github code","link_type":"OTHER","link_url":"https://github.com/RCHENLAB/HRCA_reproducibility"},{"link_name":"GSE265801","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE265801"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/4bcc16b5-7a47-45bb-b9c0-be9d5336df2d"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://rchenlab.github.io/resources/human-atlas.html"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/17265527"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/17412073"},{"link_name":"Human Retina Cell Atlas reference model","link_type":"OTHER","link_url":"https://zenodo.org/records/14014720"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/8137510"}],"name":"Single cell atlas of the human retina","published_at":"2023-11-10T21:54:15+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Jin"},{"family":"Wang","given":"Jun"},{"family":"Ibarra","given":"Ignacio L."},{"family":"Cheng","given":"Xuesen"},{"family":"Luecken","given":"Malte D."},{"family":"Lu","given":"Jiaxiong"},{"family":"Monavarfeshani","given":"Aboozar"},{"family":"Yan","given":"Wenjun"},{"family":"Zheng","given":"Yiqiao"},{"family":"Zuo","given":"Zhen"},{"family":"Colborn","given":"Samantha Lynn Zayas"},{"family":"Cortez","given":"Berenice Sarahi"},{"family":"Owen","given":"Leah A."},{"family":"Wick","given":"Brittney"},{"family":"Bao","given":"Xuan"},{"family":"Choi","given":"Jongsu"},{"family":"Haeussler","given":"Maximilian"},{"family":"Tran","given":"Nicholas M."},{"family":"Shekhar","given":"Karthik"},{"family":"Sanes","given":"Joshua R."},{"family":"Stout","given":"J. 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For detailed methods, see Zwick et al., 2023.","doi":"10.1038/s41556-023-01337-z","is_pre_analysis":false,"links":[{"link_name":"GSE201859","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201859"}],"name":"Epithelial zonation along the mammalian small intestine defines five discrete metabolic domains","published_at":"2024-07-23T18:44:52+00:00","publisher_metadata":{"authors":[{"family":"Zwick","given":"Rachel K."},{"family":"Kasparek","given":"Petr"},{"family":"Palikuqi","given":"Brisa"},{"family":"Viragova","given":"Sara"},{"family":"Weichselbaum","given":"Laura"},{"family":"McGinnis","given":"Christopher S."},{"family":"McKinley","given":"Kara L."},{"family":"Rathnayake","given":"Asoka"},{"family":"Vaka","given":"Dedeepya"},{"family":"Nguyen","given":"Vinh"},{"family":"Trentesaux","given":"Coralie"},{"family":"Reyes","given":"Efren"},{"family":"Gupta","given":"Alexander R."},{"family":"Gartner","given":"Zev 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"buccal mucosa","ontology_term_id":"UBERON:0006956","tissue_type":"tissue"},{"label":"gingiva","ontology_term_id":"UBERON:0001828","tissue_type":"tissue"},{"label":"hard palate","ontology_term_id":"UBERON:0003216","tissue_type":"tissue"},{"label":"soft palate","ontology_term_id":"UBERON:0001733","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"771c7f5e-01c9-4faf-ab7f-ee8a7cf9d285","dataset_version_id":"c85332d2-7fde-4d7f-8f34-b9d5080abd30","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"minor salivary gland","ontology_term_id":"UBERON:0001830","tissue_type":"tissue"},{"label":"parotid gland","ontology_term_id":"UBERON:0001831","tissue_type":"tissue"},{"label":"submandibular gland","ontology_term_id":"UBERON:0001736","tissue_type":"tissue"}]}],"description":"The oral and craniofacial tissues are composed of specialized niches with different functional roles including labial and buccal mucosa, periodontium and gingiva, soft and hard palate, tongue and major and minor salivary glands; supported by diverse cell types. While their function as physical barrier tissues has been extensively studied, their role in regulating immune responses for tissue homeostasis and in context of disease hasn\u2019t been fully understood. Given the cellular and spatial heterogeneity of the oral and craniofacial tissues, understanding exactly how structural immunity functions in niche specific context, with cellular and molecular comprehension of spatial disease mechanisms will open doors to future precision medicine strategies.\nHere we present the first comprehensive single-cell atlas and spatial map of cellular interactions in the oral cavity.\nThe first draft of the Oral and Craniofacial Cell Atlas focuses on healthy adult datasets to encompass a comprehensive analysis of niche-specific cells in health. We integrated 70 published and newly generated single-cell RNA sequencing datasets from 12 niches of the adult healthy oral cavity (nearly 250,000 single cells). We combined the scRNA-seq data with spatial proteomics and transcriptomics, having created two spatial atlases using a 44-plex protein panel (Multiplex Immunofluorescence, Multi-IF, using Phenocycler Fusion) and a 300-plex transcriptomics panel (MERFISH), yielding over 2 million cells from 21 samples, representing six different niches.\nThis spatial single-cell compendium of the adult oral cavity illustrates the unprecedented heterogeneity of the oral tissues in health and disease, and allowed us to uncover key cellular neighborhoods and interaction modules that regulate immune responses through structural cells. These findings have important implications for understanding the role of the oral mucosa as an innate immune organ, providing a reference for future studies on diseases that uniquely manifest in these niches.","doi":"10.1016/j.cpblue.2026.100007","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Loci-lab/Oral-Craniofacial-Atlas"}],"name":"Human Oral and Craniofacial Cell Atlas","published_at":"2024-12-16T19:41:08+00:00","publisher_metadata":{"authors":[{"family":"Matuck","given":"Bruno F."},{"family":"Huynh","given":"Khoa L.A."},{"family":"Pereira","given":"Diana"},{"family":"Easter","given":"Quinn T."},{"family":"Zhang","given":"XiuYu"},{"family":"Kunz","given":"Meik"},{"family":"Kumar","given":"Nikhil"},{"family":"Pratapa","given":"Aditya"},{"family":"Rupp","given":"Brittany T."},{"family":"Ghodke","given":"Ameer"},{"family":"Predeus","given":"Alexander V."},{"family":"Fernandes","given":"Alexandre"},{"family":"Szab\u00f3","given":"Lili"},{"family":"Hartmann","given":"Stefan"},{"family":"Harnischfeger","given":"Nadja"},{"family":"Khavandgar","given":"Zohreh"},{"family":"Beach","given":"Margaret"},{"family":"Perez","given":"Paola"},{"family":"Nilges","given":"Benedikt"},{"family":"Moreno","given":"Maria M."},{"family":"Ko","given":"Kang I."},{"family":"Singh","given":"Rohit"},{"family":"Tata","given":"Purushothama Rao"},{"family":"Teichmann","given":"Sarah A."},{"family":"Kimple","given":"Adam"},{"family":"Pringle","given":"Sarah"},{"family":"Kretzschmar","given":"Kai"},{"family":"Warner","given":"Blake M."},{"family":"Sequeira","given":"In\u00eas"},{"family":"Liu","given":"Jinze"},{"family":"Byrd","given":"Kevin M."}],"is_preprint":false,"journal":"Cell Press Blue","published_at":1775001600.0,"published_day":1,"published_month":4,"published_year":2026},"revised_at":"2026-06-11T16:53:09+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"99be70c4-e534-4413-a607-ce40b3ff2c77","collection_url":"https://cellxgene.cziscience.com/collections/99be70c4-e534-4413-a607-ce40b3ff2c77","collection_version_id":"aa6d94a0-0799-4efb-b1c7-6f1a6322ca26","consortia":[],"contact_email":"w.winuthayanon@health.missouri.edu","contact_name":"Wipawee Winuthayanon","created_at":"2026-06-10T12:16:57+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"30f5e171-83d7-4fc0-bf75-384f122346b3","dataset_version_id":"954bbfe1-2d91-456d-b1e8-61db7e30f7eb","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"fallopian tube","ontology_term_id":"UBERON:0003889","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"0f788857-3015-4fb9-912d-2545f2779c07","dataset_version_id":"1fc5cf5e-9e89-445d-9898-aa5245d7324d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"oviduct","ontology_term_id":"UBERON:0000993","tissue_type":"tissue"}]}],"description":"One of the endogenous estrogens, 17\u03b2-estradiol (E2) is a female steroid hormonesecreted from the ovary. It is well established that E2 causes biochemical and histo-logical changes in the uterus. However, it is not completely understood how E2 regu-lates the oviductal environment in vivo. In this study, we assessed the effect of E2on each oviductal cell type, using an ovariectomized-hormone-replacement mousemodel, single-cell RNA- sequencing (scRNA-seq), in situ hybridization, and cell-type- specific deletion in mice. We found that each cell type in the oviduct respondedto E2 distinctively, especially ciliated and secretory epithelial cells. The treatment ofexogenous E 2 did not drastically alter the transcriptomic profile from that of endog-enous E 2 produced during estrus. Moreover, we have identified and validated genesof interest in our datasets that may be used as cell- and region- specific markers in theoviduct. Insulin-like growth factor 1 (Igf1) was characterized as an E 2- target genein the mouse oviduct and was also expressed in human fallopian tubes. Deletion ofIgf1 in progesterone receptor (Pgr)-expressing cells resulted in female subfertility,partially due to an embryo developmental defect and embryo retention within theoviduct. In summary, we have shown that oviductal cell types, including epithelial,stromal, and muscle cells, are differentially regulated by E2 and support gene expres-sion changes, such as growth factors that are required for normal embryo develop-ment and transport in mouse models. Furthermore, we have identified cell-specificand region-specific gene markers for targeted studies and functional analysis in vivo.","doi":"10.1096/fj.202002747R","is_pre_analysis":false,"links":[{"link_name":"GSE164291","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164291"},{"link_name":"","link_type":"PROTOCOL","link_url":"https://github.com/winuthayanon/estrus/"}],"name":"Cell-type specific analysis of physiological action of estrogen inmouse oviducts","published_at":"2024-07-10T16:10:59+00:00","publisher_metadata":{"authors":[{"family":"McGlade","given":"Emily A."},{"family":"Herrera","given":"Gerardo G."},{"family":"Stephens","given":"Kalli K."},{"family":"Olsen","given":"Sierra L. W."},{"family":"Winuthayanon","given":"Sarayut"},{"family":"Guner","given":"Joie"},{"family":"Hewitt","given":"Sylvia C."},{"family":"Korach","given":"Kenneth S."},{"family":"DeMayo","given":"Francesco J."},{"family":"Lydon","given":"John P."},{"family":"Monsivais","given":"Diana"},{"family":"Winuthayanon","given":"Wipawee"}],"is_preprint":false,"journal":"The FASEB Journal","published_at":1619827200.0,"published_day":1,"published_month":5,"published_year":2021},"revised_at":"2026-06-11T16:53:11+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4f889ffc-d4bc-4748-905b-8eb9db47a2ed","collection_url":"https://cellxgene.cziscience.com/collections/4f889ffc-d4bc-4748-905b-8eb9db47a2ed","collection_version_id":"702bc4e1-0d2e-44cf-85b5-fb15703be99b","consortia":[],"contact_email":"kaistcbfg@gmail.com","contact_name":"Inkyung Jung","created_at":"2026-06-10T16:07:18+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"de2c780c-1747-40bd-9ccf-9588ec186cee","dataset_version_id":"5e491a70-a1ea-4469-9ffa-9ddff0ec3910","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"influenza","ontology_term_id":"MONDO:0005812"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Although most SARS-CoV-2-infected individuals experience mild coronavirus\ndisease 2019 (COVID-19), some patients suffer from severe COVID-19, which is\naccompanied by acute respiratory distress syndrome and systemic inflammation.\nTo identify factors driving severe progression of COVID-19, we performed\nsingle-cell RNA-seq using peripheral blood mononuclear cells (PBMCs) obtained\nfrom healthy donors, patients with mild or severe COVID-19, and patients with\nsevere influenza. Patients with COVID-19 exhibited hyper-inflammatory\nsignatures across all types of cells among PBMCs, particularly up-regulation of\nthe TNF/IL-1\u03b2-driven inflammatory response as compared to severe influenza. In\nclassical monocytes from patients with severe COVID-19, type I IFN response\nco-existed with the TNF/IL-1\u03b2-driven inflammation, and this was not seen in\npatients with milder COVID-19. Interestingly, we documented type I IFN-driven\ninflammatory features in patients with severe influenza as well. Based on this,\nwe propose that the type I IFN response plays a pivotal role in exacerbating\ninflammation in severe COVID-19.","doi":"10.1126/sciimmunol.abd1554","is_pre_analysis":false,"links":[{"link_name":"GSE149689","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE149689"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/95f07e6e-6a73-4e1b-a880-c83996b3aa5c"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-influenza-response"},{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-149689"}],"name":"Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19","published_at":"2022-01-04T20:52:24+00:00","publisher_metadata":{"authors":[{"family":"Lee","given":"Jeong Seok"},{"family":"Park","given":"Seongwan"},{"family":"Jeong","given":"Hye Won"},{"family":"Ahn","given":"Jin Young"},{"family":"Choi","given":"Seong Jin"},{"family":"Lee","given":"Hoyoung"},{"family":"Choi","given":"Baekgyu"},{"family":"Nam","given":"Su Kyung"},{"family":"Sa","given":"Moa"},{"family":"Kwon","given":"Ji-Soo"},{"family":"Jeong","given":"Su Jin"},{"family":"Lee","given":"Heung Kyu"},{"family":"Park","given":"Sung Ho"},{"family":"Park","given":"Su-Hyung"},{"family":"Choi","given":"Jun Yong"},{"family":"Kim","given":"Sung-Han"},{"family":"Jung","given":"Inkyung"},{"family":"Shin","given":"Eui-Cheol"}],"dates":["indexed: [2022, 2, 17]","published-print: [2020, 7, 3]","created: [2020, 7, 10]","deposited: [2022, 1, 13]","issued: [2020, 7, 3]","published: [2020, 7, 3]"],"is_preprint":false,"journal":"Sci. 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Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug\u2013target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.","doi":"10.1038/s41586-023-06311-1","is_pre_analysis":false,"links":[{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://www.heartcellatlas.org"},{"link_name":"multiome snRNA-seq (E-MTAB-12916)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12916"},{"link_name":"multiome snATAC-seq (E-MTAB-12919)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12919"},{"link_name":"Visium (E-MTAB-12975)","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12975"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/925f9a4c-cac0-444a-ad2c-612656ab3a85"}],"name":"Spatially resolved multiomics of human cardiac niches","published_at":"2023-10-19T10:30:29+00:00","publisher_metadata":{"authors":[{"family":"Kanemaru","given":"Kazumasa"},{"family":"Cranley","given":"James"},{"family":"Muraro","given":"Daniele"},{"family":"Miranda","given":"Antonio M. A."},{"family":"Ho","given":"Siew Yen"},{"family":"Wilbrey-Clark","given":"Anna"},{"family":"Patrick Pett","given":"Jan"},{"family":"Polanski","given":"Krzysztof"},{"family":"Richardson","given":"Laura"},{"family":"Litvinukova","given":"Monika"},{"family":"Kumasaka","given":"Natsuhiko"},{"family":"Qin","given":"Yue"},{"family":"Jablonska","given":"Zuzanna"},{"family":"Semprich","given":"Claudia I."},{"family":"Mach","given":"Lukas"},{"family":"Dabrowska","given":"Monika"},{"family":"Richoz","given":"Nathan"},{"family":"Bolt","given":"Liam"},{"family":"Mamanova","given":"Lira"},{"family":"Kapuge","given":"Rakeshlal"},{"family":"Barnett","given":"Sam N."},{"family":"Perera","given":"Shani"},{"family":"Talavera-L\u00f3pez","given":"Carlos"},{"family":"Mulas","given":"Ilaria"},{"family":"Mahbubani","given":"Krishnaa T."},{"family":"Tuck","given":"Liz"},{"family":"Wang","given":"Lu"},{"family":"Huang","given":"Margaret M."},{"family":"Prete","given":"Martin"},{"family":"Pritchard","given":"Sophie"},{"family":"Dark","given":"John"},{"family":"Saeb-Parsy","given":"Kourosh"},{"family":"Patel","given":"Minal"},{"family":"Clatworthy","given":"Menna R."},{"family":"H\u00fcbner","given":"Norbert"},{"family":"Chowdhury","given":"Rasheda A."},{"family":"Noseda","given":"Michela"},{"family":"Teichmann","given":"Sarah A."}],"is_preprint":false,"journal":"Nature","published_at":1690416000.0,"published_day":27,"published_month":7,"published_year":2023},"revised_at":"2026-06-11T16:53:18+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"62e8f058-9c37-48bc-9200-e767f318a8ec","collection_url":"https://cellxgene.cziscience.com/collections/62e8f058-9c37-48bc-9200-e767f318a8ec","collection_version_id":"8ce8079e-322a-4cef-a8a3-61c84c98a71a","consortia":["Human Tumor Atlas Network (HTAN)"],"contact_email":"chanj3@mskcc.org","contact_name":"Joseph 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The SCLC and LUAD cohorts include treated and untreated patients. Samples were obtained from primary tumors, regional lymph node metastases, and distant metastases (liver, adrenal gland, axilla, and pleural effusion). This data was generated as part of the NCI Human Tumor Atlas Network. (Grant Number:  1U2CCA233284-01).","doi":"10.1016/j.ccell.2021.09.008","is_pre_analysis":false,"links":[{"link_name":"data.humantumoratlas.org","link_type":"OTHER","link_url":"https://data.humantumoratlas.org/explore?selectedFilters=%5B%7B%22group%22%3A%22AtlasName%22%2C%22value%22%3A%22HTAN+MSK%22%7D%2C%7B%22value%22%3A%22hdf5%22%2C%22label%22%3A%22hdf5%22%2C%22group%22%3A%22FileFormat%22%2C%22count%22%3A11%2C%22isSelected%22%3Afalse%7D%5D&tab=file"},{"link_name":"phs002371","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002371"}],"name":"HTAN MSK - Single cell profiling reveals novel tumor and myeloid subpopulations in small cell lung cancer","published_at":"2022-06-03T15:37:48+00:00","publisher_metadata":{"authors":[{"family":"Chan","given":"Joseph M."},{"family":"Quintanal-Villalonga","given":"\u00c1lvaro"},{"family":"Gao","given":"Vianne Ran"},{"family":"Xie","given":"Yubin"},{"family":"Allaj","given":"Viola"},{"family":"Chaudhary","given":"Ojasvi"},{"family":"Masilionis","given":"Ignas"},{"family":"Egger","given":"Jacklynn"},{"family":"Chow","given":"Andrew"},{"family":"Walle","given":"Thomas"},{"family":"Mattar","given":"Marissa"},{"family":"Yarlagadda","given":"Dig V.K."},{"family":"Wang","given":"James L."},{"family":"Uddin","given":"Fathema"},{"family":"Offin","given":"Michael"},{"family":"Ciampricotti","given":"Metamia"},{"family":"Qeriqi","given":"Besnik"},{"family":"Bahr","given":"Amber"},{"family":"de Stanchina","given":"Elisa"},{"family":"Bhanot","given":"Umesh K."},{"family":"Lai","given":"W. Victoria"},{"family":"Bott","given":"Matthew J."},{"family":"Jones","given":"David R."},{"family":"Ruiz","given":"Arvin"},{"family":"Baine","given":"Marina K."},{"family":"Li","given":"Yanyun"},{"family":"Rekhtman","given":"Natasha"},{"family":"Poirier","given":"John T."},{"family":"Nawy","given":"Tal"},{"family":"Sen","given":"Triparna"},{"family":"Mazutis","given":"Linas"},{"family":"Hollmann","given":"Travis J."},{"family":"Pe'er","given":"Dana"},{"family":"Rudin","given":"Charles M."}],"is_preprint":false,"journal":"Cancer Cell","published_at":1635724800.0,"published_day":1,"published_month":11,"published_year":2021},"revised_at":"2026-06-11T16:53:25+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"afd343f4-bb60-4632-9902-73a4a1ff1557","collection_url":"https://cellxgene.cziscience.com/collections/afd343f4-bb60-4632-9902-73a4a1ff1557","collection_version_id":"9a43730d-4c8c-4d58-b5c6-1ba849969e79","consortia":["GenitoUrinary Development Molecular Anatomy Project (GUDMAP)"],"contact_email":"ahting@mdanderson.org","contact_name":"Angela Ting","created_at":"2026-06-10T05:01:32+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"fb5eeccf-3c2a-473c-b6e3-7a1dda18d42d","dataset_version_id":"1352a8d5-e392-4e1d-8acd-c47f3c93f22e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"dome of urinary bladder","ontology_term_id":"UBERON:8600049","tissue_type":"tissue"},{"label":"neck of urinary bladder","ontology_term_id":"UBERON:0001258","tissue_type":"tissue"},{"label":"ureteral orifice","ontology_term_id":"UBERON:0012303","tissue_type":"tissue"},{"label":"ureterovesical junction","ontology_term_id":"UBERON:0009973","tissue_type":"tissue"}]}],"description":"Bladder function relies on coordinated interactions among epithelial, stromal, vascular, and neural compartments, but high-resolution molecular and spatial features remain undefined. We generated a publicly accessible, poly(A) isoform\u2013aware single-nucleus and spatial reference of the adult human bladder spanning four anatomical regions and both sexes. Integrating 74,694 snRNA-seq profiles with 168,476 Xenium-resolved cells, we identified 22 cell types and 23,489 polyadenylation sites, with isoform usage improving stromal resolution beyond gene expression alone. Spatial mapping revealed layered fibroblast niches aligned with epithelial, vascular, and neural structures, supported by Visium data. This multimodal reference links isoform regulation to anatomical context and provides a reusable framework for cell-type annotation, cross-study integration, and analyses of bladder physiology and disease.","doi":"10.64898/2025.12.18.695268","is_pre_analysis":false,"links":[{"link_name":"GSE267964","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE267964"},{"link_name":"GSE270225","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE270225"}],"name":"A poly(A) isoform\u2013aware single-cell and spatial atlas defines fibroblast niches in the human bladder","published_at":"2026-05-06T23:37:06+00:00","publisher_metadata":{"authors":[{"family":"Santo","given":"Briana A."},{"family":"Fink","given":"Emily E."},{"family":"Desprez","given":"Pierre-Emmanuel"},{"family":"Lin","given":"Yi-Chia"},{"family":"Eltemamy","given":"Mohamed"},{"family":"Wee","given":"Alvin"},{"family":"Le","given":"Ninh B."},{"family":"Krylova","given":"Alexandra"},{"family":"Tran","given":"Uyen"},{"family":"Kochat","given":"Veena"},{"family":"Rai","given":"Kunal"},{"family":"Strand","given":"Douglas W."},{"family":"Wessely","given":"Oliver"},{"family":"Lee","given":"Byron H."},{"family":"Ting","given":"Angela H."}],"is_preprint":true,"journal":"bioRxiv","published_at":1766016000.0,"published_day":18,"published_month":12,"published_year":2025},"revised_at":"2026-06-11T16:53:26+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"5f80428b-222d-450b-a7de-a408186ceb86","collection_url":"https://cellxgene.cziscience.com/collections/5f80428b-222d-450b-a7de-a408186ceb86","collection_version_id":"cbd792bb-e903-4856-a7e7-f75ee8a6bf83","consortia":[],"contact_email":"rv4@sanger.ac.uk","contact_name":"Roser Vento-Tormo","created_at":"2026-06-10T06:09:34+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"3966ba97-beb8-4d0b-9954-d3775cd2cd61","dataset_version_id":"38b64997-4c91-47f0-b421-c4a944a93ae8","disease":[{"label":"Plasmodium malariae malaria","ontology_term_id":"MONDO:0001943"},{"label":"listeriosis","ontology_term_id":"MONDO:0005828"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"toxoplasmosis","ontology_term_id":"MONDO:0005989"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"placenta","ontology_term_id":"UBERON:0001987","tissue_type":"tissue"}]}],"description":"The placenta is a selective maternal-fetal barrier that provides nourishment and protection from infections. However, certain pathogens can attach to and even cross the placenta, causing pregnancy complications with potential lifelong impacts on the child\u2019s health. Here, we profiled at the single-cell level the placental responses to three pathogens associated with intrauterine complications\u2014Plasmodium falciparum, Listeria monocytogenes, and Toxoplasma gondii. We found that upon exposure to the pathogens, all placental lineages trigger inflammatory responses that may compromise placental function. Additionally, we characterized the responses of fetal macrophages known as Hofbauer cells (HBCs) to each pathogen and propose that they are the probable niche for T. gondii. Finally, we revealed how P. falciparum adapts to the placental microenvironment by modulating protein export into the host erythrocyte and nutrient uptake pathways. Altogether, we have defined the cellular networks and signaling pathways mediating acute placental inflammatory responses that could contribute to pregnancy complications.","doi":"10.1016/j.cels.2024.04.002","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-12795"},{"link_name":"reproductivecellatlas","link_type":"DATA_SOURCE","link_url":"https://www.reproductivecellatlas.org"}],"name":"Acute response to pathogens in the early human placenta at single-cell resolution","published_at":"2024-05-07T14:28:35+00:00","publisher_metadata":{"authors":[{"family":"Hoo","given":"Regina"},{"family":"Ruiz-Morales","given":"Elias R."},{"family":"Kelava","given":"Iva"},{"family":"Rawat","given":"Mukul"},{"family":"Mazzeo","given":"Cecilia Icoresi"},{"family":"Tuck","given":"Elizabeth"},{"family":"Sancho-Serra","given":"Carmen"},{"family":"Chelaghma","given":"Sara"},{"family":"Predeus","given":"Alexander V."},{"family":"Murray","given":"Simon"},{"family":"Fernandez-Antoran","given":"David"},{"family":"Waller","given":"Ross F."},{"family":"\u00c1lvarez-Errico","given":"Damiana"},{"family":"Lee","given":"Marcus C.S."},{"family":"Vento-Tormo","given":"Roser"}],"is_preprint":false,"journal":"Cell Systems","published_at":1714521600.0,"published_day":1,"published_month":5,"published_year":2024},"revised_at":"2026-06-11T16:53:16+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"20a1dadf-a3a7-4783-b311-fcff3c457763","collection_url":"https://cellxgene.cziscience.com/collections/20a1dadf-a3a7-4783-b311-fcff3c457763","collection_version_id":"8ceefe2e-1041-4bbe-9e46-ea5a7d819f9f","consortia":[],"contact_email":"astolias@bcm.edu","contact_name":"Andreas S. Tolias","created_at":"2026-06-10T06:33:42+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"cb5efdb0-f91c-4cbd-9ad4-9d4fa41c572d","dataset_version_id":"bd7c4cc1-4c94-4f7a-93c2-4eee5311c8ca","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]},{"assay":[{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"bf6a5c78-5a2e-4e34-93f3-7be5d127d879","dataset_version_id":"b8ad0698-8afb-491b-ad61-4efa3bd01790","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"9bb9596d-f23f-4558-912f-d4dc7d52721b","dataset_version_id":"b83d911c-430b-407f-9d40-9a0dcccee2c3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]},{"assay":[{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"8f98c236-43f0-4dc4-985b-c304499f7b44","dataset_version_id":"89342c93-7431-4d87-82e8-c01129164785","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"42ff5b55-b848-4f4c-b7cb-b8aac107841c","dataset_version_id":"4d8d7b48-31b8-47ee-ba50-ca8eeff25543","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]},{"assay":[{"label":"Patch-seq","ontology_term_id":"EFO:0008853"}],"dataset_id":"341a0702-9d26-4d8a-b047-ab475f3b492e","dataset_version_id":"e77d5496-84ab-47e0-8bbe-9914bbccf523","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"primary motor cortex","ontology_term_id":"UBERON:0001384","tissue_type":"tissue"}]}],"description":"Cortical neurons exhibit extreme diversity in gene expression as well as in morphological and electrophysiological properties. Most existing neural taxonomies are based on either transcriptomic or morpho-electric criteria, as it has been technically challenging to study both aspects of neuronal diversity in the same set of cells. Here we used Patch-seq to combine patch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in adult mouse primary motor cortex, providing a morpho-electric annotation of almost all transcriptomically defined neural cell types. We found that, although broad families of transcriptomic types (those expressing Vip, Pvalb, Sst and so on) had distinct and essentially non-overlapping morpho-electric phenotypes, individual transcriptomic types within the same family were not well separated in the morpho-electric space. Instead, there was a continuum of variability in morphology and electrophysiology, with neighbouring transcriptomic cell types showing similar morpho-electric features, often without clear boundaries between them. Our results suggest that neuronal types in the neocortex do not always form discrete entities. Instead, neurons form a hierarchy that consists of distinct non-overlapping branches at the level of families, but can form continuous and correlated transcriptomic and morpho-electrical landscapes within families.","doi":"10.1038/s41586-020-2907-3","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://toliaslab.org/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://assets.nemoarchive.org/dat-kq04hua"}],"name":"Phenotypic variation of transcriptomic cell types in mouse motor cortex","published_at":"2022-06-16T22:32:03+00:00","publisher_metadata":{"authors":[{"family":"Scala","given":"Federico"},{"family":"Kobak","given":"Dmitry"},{"family":"Bernabucci","given":"Matteo"},{"family":"Bernaerts","given":"Yves"},{"family":"Cadwell","given":"Cathryn Ren\u00e9"},{"family":"Castro","given":"Jesus Ramon"},{"family":"Hartmanis","given":"Leonard"},{"family":"Jiang","given":"Xiaolong"},{"family":"Laturnus","given":"Sophie"},{"family":"Miranda","given":"Elanine"},{"family":"Mulherkar","given":"Shalaka"},{"family":"Tan","given":"Zheng Huan"},{"family":"Yao","given":"Zizhen"},{"family":"Zeng","given":"Hongkui"},{"family":"Sandberg","given":"Rickard"},{"family":"Berens","given":"Philipp"},{"family":"Tolias","given":"Andreas S."}],"dates":["indexed: [2022, 2, 17]","published-print: [2021, 10, 7]","created: [2020, 11, 12]","published-online: [2020, 11, 12]","deposited: [2021, 10, 8]","issued: [2020, 11, 12]","published: [2020, 11, 12]"],"is_preprint":false,"journal":"Nature","published_day":7,"published_month":10,"published_year":2021},"revised_at":"2026-06-11T16:53:17+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"fc77d2ae-247d-44d7-aa24-3f4859254c2c","collection_url":"https://cellxgene.cziscience.com/collections/fc77d2ae-247d-44d7-aa24-3f4859254c2c","collection_version_id":"555d96a2-f7de-4ece-b4db-339318f76cb2","consortia":["CZI Cell Science"],"contact_email":"qianyi.ma@umich.edu","contact_name":"Qianyi Ma","created_at":"2026-06-10T00:31:45+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"cac02b79-9f54-4668-9235-60d3b76a4197","dataset_version_id":"8e83e691-0abd-449f-a239-279e3527c713","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo 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of fallopian tube","ontology_term_id":"UBERON:0016632","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"03c544fb-a103-4d18-9230-eae9cfee3af2","dataset_version_id":"f378fa91-16cb-42df-a1cb-b841d574acfc","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"ampulla of fallopian tube","ontology_term_id":"UBERON:0012648","tissue_type":"tissue"},{"label":"fallopian tube","ontology_term_id":"UBERON:0003889","tissue_type":"tissue"},{"label":"fimbria of fallopian tube","ontology_term_id":"UBERON:8410010","tissue_type":"tissue"},{"label":"isthmus of fallopian tube","ontology_term_id":"UBERON:0016632","tissue_type":"tissue"}]}],"description":"Fallopian tube (FT) homeostasis requires dynamic regulation of heterogeneous cell populations and is disrupted in infertility and ovarian cancer. Here we applied single-cell RNA-seq to profile 59,738 FT cells from 4 healthy pre-menopausal subjects. The resulting cell atlas contains 12 major cell types representing epithelial, stromal and immune compartments. Re-clustering of epithelial cells identified 4 ciliated and 6 non-ciliated secretory epithelial subtypes, two of which represent potential progenitor pools: one leading to mature secretory cells, while the other contributing to either ciliated cells or one of the stromal cell types. To understand how FT cell numbers and states change in a disease state, we analyzed 17,798 cells from two hydrosalpinx samples and observed shifts in epithelial and stromal populations, and cell type-specific changes in extracellular matrix and TGF-\u03b2 signaling, underscoring fibrosis pathophysiology. This resource is expected to facilitate future studies to understand fallopian tube homeostasis in normal development and disease.","doi":"10.1101/2021.09.16.460628","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/21ea8ddb-525f-4f1f-a820-31f0360399a2"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178101"}],"name":"Cellular heterogeneity of human fallopian tubes in normal and hydrosalpinx disease states identified by scRNA-seq","published_at":"2022-01-24T16:58:54+00:00","publisher_metadata":{"authors":[{"family":"Ulrich","given":"Nicole D"},{"family":"Shen","given":"Yu-chi"},{"family":"Ma","given":"Qianyi"},{"family":"Yang","given":"Kun"},{"family":"Hannum","given":"D Ford"},{"family":"Jones","given":"Andrea"},{"family":"Machlin","given":"Jordan"},{"family":"Randolph","given":"John F"},{"family":"Smith","given":"Yolanda R"},{"family":"Schon","given":"Samantha B"},{"family":"Shikanov","given":"Ariella"},{"family":"Marsh","given":"Erica E."},{"family":"Li","given":"Jun Z"},{"family":"Hammoud","given":"Sue"}],"is_preprint":true,"journal":"bioRxiv","published_at":1631836800.0,"published_day":17,"published_month":9,"published_year":2021},"revised_at":"2026-06-11T16:53:19+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"45f0f67d-4b69-4a3c-a4e8-a63b962e843f","collection_url":"https://cellxgene.cziscience.com/collections/45f0f67d-4b69-4a3c-a4e8-a63b962e843f","collection_version_id":"dec05229-b60d-47a1-9095-da43dc1fc20e","consortia":["Allen Institute for Brain Science","BRAIN Initiative"],"contact_email":"bosiljkat@alleninstitute.org","contact_name":"Bosiljka Tasic","created_at":"2026-06-10T03:44:05+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"Smart-seq v4","ontology_term_id":"EFO:0700016"}],"dataset_id":"28c696bb-9549-434b-9340-dc745a846f9a","dataset_version_id":"cee4ade6-1acb-46d5-a9d5-503b598b9f5c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"frontal cortex","ontology_term_id":"UBERON:0001870","tissue_type":"tissue"},{"label":"primary visual cortex","ontology_term_id":"UBERON:0002436","tissue_type":"tissue"}]}],"description":"The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (\u03b3-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex. [Excerpt from publication's abstract]","doi":"10.1038/s41586-018-0654-5","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/AllenInstitute/tasic2018analysis/"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/AllenInstitute/scrattch.hicat"},{"link_name":"GSE115746","link_type":"RAW_DATA","link_url":"http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115746"},{"link_name":"Cell Types Database: RNA-Seq Data","link_type":"OTHER","link_url":"https://portal.brain-map.org/atlases-and-data/rnaseq"}],"name":"Shared and distinct transcriptomic cell types across neocortical areas","published_at":"2021-03-08T20:10:16+00:00","publisher_metadata":{"authors":[{"family":"Tasic","given":"Bosiljka"},{"family":"Yao","given":"Zizhen"},{"family":"Graybuck","given":"Lucas T."},{"family":"Smith","given":"Kimberly A."},{"family":"Nguyen","given":"Thuc 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development","doi":"10.1038/s41588-025-02083-8","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/DiseaseNeuroGenomics/snMultiome"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://nda.nih.gov/edit_collection.html?id=5371"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/14421659"},{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/12752107"}],"name":"Simultaneous profiling of transcription and chromatin accessibility at the single-cell level for postnatal human brain development","published_at":"2025-01-31T20:38:53+00:00","publisher_metadata":{"authors":[{"family":"Clarence","given":"Tereza"},{"family":"Bendl","given":"Jaroslav"},{"family":"Cao","given":"Xuan"},{"family":"Wang","given":"Xinyi"},{"family":"Zheng","given":"Shiwei"},{"family":"Hoffman","given":"Gabriel 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This atlas spans sc/snRNA-seq of 505,256 lung cells from 148 normal human lung samples from 104 donors from parenchyma, trachea, bonchi, bronchus SMG and small airway.","doi":"10.1038/s41467-023-40173-5","is_pre_analysis":false,"links":[{"link_name":"Study Browser","link_type":"LAB_WEBSITE","link_url":"https://lungmap.net/cell-cards/"},{"link_name":"LGEA","link_type":"OTHER","link_url":"https://research.cchmc.org/pbge/lunggens/tools/lung_at_glance.html?tab=reference&species=Human"}],"name":"Human CellCards Multi-Study CellRef 1.0 Atlas","published_at":"2024-06-18T18:42:27+00:00","publisher_metadata":{"authors":[{"family":"Guo","given":"Minzhe"},{"family":"Morley","given":"Michael P."},{"family":"Jiang","given":"Cheng"},{"family":"Wu","given":"Yixin"},{"family":"Li","given":"Guangyuan"},{"family":"Du","given":"Yina"},{"family":"Zhao","given":"Shuyang"},{"family":"Wagner","given":"Andrew"},{"family":"Cakar","given":"Adnan Cihan"},{"family":"Kouril","given":"Michal"},{"family":"Jin","given":"Kang"},{"family":"Gaddis","given":"Nathan"},{"family":"Kitzmiller","given":"Joseph A."},{"family":"Stewart","given":"Kathleen"},{"family":"Basil","given":"Maria C."},{"family":"Lin","given":"Susan M."},{"family":"Ying","given":"Yun"},{"family":"Babu","given":"Apoorva"},{"family":"Wikenheiser-Brokamp","given":"Kathryn A."},{"family":"Mun","given":"Kyu Shik"},{"family":"Naren","given":"Anjaparavanda P."},{"family":"Clair","given":"Geremy"},{"family":"Adkins","given":"Joshua N."},{"family":"Pryhuber","given":"Gloria S."},{"family":"Misra","given":"Ravi S."},{"family":"Aronow","given":"Bruce J."},{"family":"Tickle","given":"Timothy L."},{"family":"Salomonis","given":"Nathan"},{"family":"Sun","given":"Xin"},{"family":"Morrisey","given":"Edward E."},{"family":"Whitsett","given":"Jeffrey A."},{"family":"Lin","given":"Sara"},{"family":"Xu","given":"Yan"},{"name":"NHLBI LungMAP Consortium"}],"is_preprint":false,"journal":"Nat Commun","published_at":1690588800.0,"published_day":29,"published_month":7,"published_year":2023},"revised_at":"2026-06-11T16:53:24+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"73cf6939-3caa-4105-bc57-e073ee885a28","collection_url":"https://cellxgene.cziscience.com/collections/73cf6939-3caa-4105-bc57-e073ee885a28","collection_version_id":"3276a66a-af66-44fe-a861-de39e390b789","consortia":["Human Cell Atlas (HCA)"],"contact_email":"zaragosi@ipmc.cnrs.fr","contact_name":"Laure-Emmanuelle Zaragosi","created_at":"2026-06-10T00:49:22+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"c69fb6cd-fc4d-4216-85cb-8d80e7771786","dataset_version_id":"081fef14-662c-430d-888f-b87a701d86b3","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"epithelial cell of lung","ontology_term_id":"CL:0000082","tissue_type":"primary cell culture"}]}],"description":"The human airway mucociliary epithelium can be recapitulated in vitro using primary cells cultured in an Air-Liquid Interface (ALI), a reliable surrogate to perform pathophysiological studies. As tremendous variations exist between media used for ALI-cultured human airway epithelial cells, our study aimed to evaluate the impact of several media (BEGM, PneumaCult, \u201cHalf&Half\u201d and \u201cClancy\u201d) on cell type distribution using single-cell RNA sequencing and imaging. Our work revealed the impact of these media on cell composition, gene expression profile, cell signaling or epithelial shape. We found higher proportions of multiciliated cells in PneumaCultTM-ALI and Half&Half, stronger EGF signaling from basal cells in BEGM-ALI, differential expression of the SARS-CoV-2 entry factor ACE2, and distinct secretome transcripts depending on media used. We also established that proliferation in PneumaCult-Ex Plus favored secretory cell fate, showing the key influence of proliferation media on late differentiation epithelial characteristics. Altogether, our data offer a comprehensive repertoire for evaluating the effects of culture conditions on airway epithelial differentiation and will help to choose the most relevant medium according to the processes to be investigated such as cilia, mucus biology or viral infection. We detail useful parameters that should be explored to document airway epithelial cell fate and shaping.","doi":"10.1165/rcmb.2023-0356MA","is_pre_analysis":false,"links":[{"link_name":"GSE243045","link_type":"OTHER","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE243045"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD00001011362"}],"name":"Cell culture differentiation and proliferation conditions influence the in vitro regeneration of the human airway epithelium","published_at":"2024-10-10T17:43:40+00:00","publisher_metadata":{"authors":[{"family":"Redman","given":"Elisa"},{"family":"Fierville","given":"Morgane"},{"family":"Cavard","given":"Am\u00e9lie"},{"family":"Plaisant","given":"Magali"},{"family":"Arguel","given":"Marie-Jeanne"},{"family":"Ruiz Garcia","given":"Sandra"},{"family":"McAndrew","given":"Eamon M."},{"family":"Girard-Riboulleau","given":"C\u00e9dric"},{"family":"Lebrigand","given":"Kevin"},{"family":"Magnone","given":"Virginie"},{"family":"Ponzio","given":"Gilles"},{"family":"Gras","given":"Delphine"},{"family":"Chanez","given":"Pascal"},{"family":"Abelanet","given":"Sophie"},{"family":"Barbry","given":"Pascal"},{"family":"Marcet","given":"Brice"},{"family":"Zaragosi","given":"Laure-Emmanuelle"}],"is_preprint":false,"journal":"American Journal of Respiratory Cell and Molecular Biology","published_at":1725148800.0,"published_day":1,"published_month":9,"published_year":2024},"revised_at":"2026-06-11T16:53:29+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"579203e2-182f-47bc-8230-7aa47247e2a4","collection_url":"https://cellxgene.cziscience.com/collections/579203e2-182f-47bc-8230-7aa47247e2a4","collection_version_id":"56adb25b-2cd5-4535-bde3-6212e74a68e0","consortia":["CZI Cell Science"],"contact_email":"sarah.snelling@ndorms.ox.ac.uk","contact_name":"Sarah Snelling","created_at":"2026-06-10T05:10:19+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"acd544d0-4d8b-46c7-98b3-fc48f7e6fdb7","dataset_version_id":"2df978a2-4a88-4880-8a7c-cf495bf250d9","disease":[{"label":"injury","ontology_term_id":"MONDO:0021178"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"tendon of quadriceps femoris","ontology_term_id":"UBERON:0014848","tissue_type":"tissue"}]}],"description":"Tendon ruptures in humans have regularly been studied during the chronic phase of injury, in particular rotator cuff disease. However, the early response to acute tendon ruptures remains less investigated. Quadriceps tendons, which require prompt surgical treatment, offer a model to investigate this early response. Therefore, this study aimed to explore the early cellular changes in ruptured compared to healthy human quadriceps tendons. Quadriceps tendon samples were collected from patients undergoing fracture repair (healthy) or tendon repair surgery (collected 7-8 days post-injury). Nuclei were isolated for single-nucleus RNA sequencing, and comprehensive transcriptomic analysis was conducted. The transcriptomes of 12,808 nuclei (7,268 from healthy and 5,540 from ruptured quadriceps tendons) were profiled, revealing 12 major cell types and several cell subtypes and states. Rupture samples showed increased expression of genes related to extracellular matrix organisation and cell cycle signalling, and a decrease in expression of genes in lipid metabolism pathways. These changes were predominantly driven by gene expression changes in the fibroblast, vascular endothelial cells (VECs), mural cell, and macrophage populations: fibroblasts shift to an activated phenotype upon rupture and there is an increase in proportion of capillary and dividing VECs, suggesting an angiogenic response. A diverse immune environment was observed, with a shift from homeostatic to activated macrophages following rupture. Cell-cell interactions increased in number and diversity in rupture, and primarily involved fibroblast and VEC populations. Collectively, this transcriptomic analysis suggests that fibroblasts and endothelial cells are key orchestrators of the early injury response within ruptured quadriceps tendon.","doi":"10.1113/JP287812","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Botnar-MSK-Atlas/quadriceps_tendon_atlas/"},{"link_name":"Human Cell Atlas","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/8dcbd84a-6243-4501-a684-0dcd084bb536"}],"name":"Exploring cellular changes in ruptured human quadriceps tendons at single-cell resolution","published_at":"2025-05-07T20:41:53+00:00","publisher_metadata":{"authors":[{"family":"Mimpen","given":"Jolet Y."},{"family":"Baldwin","given":"Mathew J."},{"family":"Paul","given":"Claudia"},{"family":"Ramos\u2010Mucci","given":"Lorenzo"},{"family":"Kurjan","given":"Alina"},{"family":"Cohen","given":"Carla J."},{"family":"Sharma","given":"Shreeya"},{"family":"Chevalier Florquin","given":"Marie S. 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sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"diencephalon","ontology_term_id":"UBERON:0001894","tissue_type":"tissue"},{"label":"hindbrain","ontology_term_id":"UBERON:0002028","tissue_type":"tissue"},{"label":"medulla oblongata","ontology_term_id":"UBERON:0001896","tissue_type":"tissue"},{"label":"midbrain","ontology_term_id":"UBERON:0001891","tissue_type":"tissue"},{"label":"pons","ontology_term_id":"UBERON:0000988","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"4398dcfc-f86b-4d52-aa9f-1f2cf902c0cf","dataset_version_id":"ecaf3bd4-55a8-471a-9d94-bc3d64dae249","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"diencephalon","ontology_term_id":"UBERON:0001894","tissue_type":"tissue"},{"label":"hindbrain","ontology_term_id":"UBERON:0002028","tissue_type":"tissue"},{"label":"medulla oblongata","ontology_term_id":"UBERON:0001896","tissue_type":"tissue"},{"label":"midbrain","ontology_term_id":"UBERON:0001891","tissue_type":"tissue"},{"label":"pons","ontology_term_id":"UBERON:0000988","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"2ad168af-ae8c-469e-b21f-dd7f93146d7e","dataset_version_id":"274ed523-78e7-4ea5-85ec-b91a17497fbb","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"diencephalon","ontology_term_id":"UBERON:0001894","tissue_type":"tissue"},{"label":"hindbrain","ontology_term_id":"UBERON:0002028","tissue_type":"tissue"},{"label":"medulla oblongata","ontology_term_id":"UBERON:0001896","tissue_type":"tissue"},{"label":"midbrain","ontology_term_id":"UBERON:0001891","tissue_type":"tissue"},{"label":"pons","ontology_term_id":"UBERON:0000988","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"19f1bec6-eeb7-4133-accc-992d745fef89","dataset_version_id":"e88a34d0-d28a-4d10-a8c5-d59f86ba621a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"diencephalon","ontology_term_id":"UBERON:0001894","tissue_type":"tissue"},{"label":"hindbrain","ontology_term_id":"UBERON:0002028","tissue_type":"tissue"},{"label":"medulla oblongata","ontology_term_id":"UBERON:0001896","tissue_type":"tissue"},{"label":"midbrain","ontology_term_id":"UBERON:0001891","tissue_type":"tissue"},{"label":"pons","ontology_term_id":"UBERON:0000988","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"}]},{"assay":[{"label":"10x multiome","ontology_term_id":"EFO:0030059"}],"dataset_id":"00f15b43-f871-46d8-8105-814387ad8658","dataset_version_id":"dc94c601-b19e-405b-a2aa-3f51554de0de","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"brain","ontology_term_id":"UBERON:0000955","tissue_type":"tissue"},{"label":"cerebellum","ontology_term_id":"UBERON:0002037","tissue_type":"tissue"},{"label":"diencephalon","ontology_term_id":"UBERON:0001894","tissue_type":"tissue"},{"label":"hindbrain","ontology_term_id":"UBERON:0002028","tissue_type":"tissue"},{"label":"medulla oblongata","ontology_term_id":"UBERON:0001896","tissue_type":"tissue"},{"label":"midbrain","ontology_term_id":"UBERON:0001891","tissue_type":"tissue"},{"label":"pons","ontology_term_id":"UBERON:0000988","tissue_type":"tissue"},{"label":"telencephalon","ontology_term_id":"UBERON:0001893","tissue_type":"tissue"}]}],"description":"The human brain develops through a tightly organized cascade of patterning events, induced by transcription factor expression and changes in chromatin accessibility. Although gene expression across the developing brain has been described at single-cell resolution1, similar atlases of chromatin accessibility have been primarily focused on the forebrain2,3,4. Here we describe chromatin accessibility and paired gene expression across the entire developing human brain during the first trimester (6\u201313 weeks after conception). We defined 135 clusters and used multiomic measurements to link candidate cis-regulatory elements to gene expression. The number of accessible regions increased both with age and along neuronal differentiation. Using a convolutional neural network, we identified putative functional transcription factor-binding sites in enhancers characterizing neuronal subtypes. We applied this model to cis-regulatory elements linked to ESRRB to elucidate its activation mechanism in the Purkinje cell lineage. Finally, by linking disease-associated single nucleotide polymorphisms to cis-regulatory elements, we validated putative pathogenic mechanisms in several diseases and identified midbrain-derived GABAergic neurons as being the most vulnerable to major depressive disorder-related mutations. Our findings provide a more detailed view of key gene regulatory mechanisms underlying the emergence of brain cell types during the first trimester and a comprehensive reference for future studies related to human neurodevelopment.","doi":"10.1038/s41586-024-07234-1","is_pre_analysis":false,"links":[{"link_name":"EGAS00001007472","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001007472"},{"link_name":"Github","link_type":"OTHER","link_url":"https://github.com/linnarsson-lab/fetal_brain_multiomics"}],"name":"Chromatin accessibility during human first-trimester neurodevelopment","published_at":"2025-07-30T18:48:14+00:00","publisher_metadata":{"authors":[{"family":"Mannens","given":"Camiel C. A."},{"family":"Hu","given":"Lijuan"},{"family":"L\u00f6nnerberg","given":"Peter"},{"family":"Schipper","given":"Marijn"},{"family":"Reagor","given":"Caleb C."},{"family":"Li","given":"Xiaofei"},{"family":"He","given":"Xiaoling"},{"family":"Barker","given":"Roger A."},{"family":"Sundstr\u00f6m","given":"Erik"},{"family":"Posthuma","given":"Danielle"},{"family":"Linnarsson","given":"Sten"}],"is_preprint":false,"journal":"Nature","published_at":1762387200.0,"published_day":6,"published_month":11,"published_year":2025},"revised_at":"2026-06-11T16:53:33+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3f50314f-bdc9-40c6-8e4a-b0901ebfbe4c","collection_url":"https://cellxgene.cziscience.com/collections/3f50314f-bdc9-40c6-8e4a-b0901ebfbe4c","collection_version_id":"3274962b-40ba-4543-82fe-9dc898416bb3","consortia":[],"contact_email":"hakimia@mskcc.org","contact_name":"A. Ari Hakimi","created_at":"2026-06-10T15:09:48+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 5' v2","ontology_term_id":"EFO:0009900"}],"dataset_id":"bd65a70f-b274-4133-b9dd-0d1431b6af34","dataset_version_id":"6602fa5a-d663-4fe0-8dc3-90191c3a013b","disease":[{"label":"clear cell renal carcinoma","ontology_term_id":"MONDO:0005005"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"lymph node","ontology_term_id":"UBERON:0000029","tissue_type":"tissue"}]}],"description":"Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated, but the effect of immune heterogeneity on clinical outcome in ccRCC has not been fully characterized. Here we perform paired single-cell RNA (scRNA) and T cell receptor (TCR) sequencing of 167,283 cells from multiple tumor regions, lymph node, normal kidney, and peripheral blood of two immune checkpoint blockade (ICB)-na\u00efve and four ICB-treated patients to map the ccRCC immune landscape. We detect extensive heterogeneity within and between patients, with enrichment of CD8A+ tissue-resident T cells in a patient responsive to ICB and tumor-associated macrophages (TAMs) in a resistant patient. A TCR trajectory framework suggests distinct T cell differentiation pathways between patients responding and resistant to ICB. Finally, scRNA-derived signatures of tissue-resident T cells and TAMs are associated with response to ICB and targeted therapies across multiple independent cohorts. Our study establishes a multimodal interrogation of the cellular programs underlying therapeutic efficacy in ccRCC.","doi":"10.1016/j.ccell.2021.03.007","is_pre_analysis":false,"links":[{"link_name":"PRJNA705464","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA705464"},{"link_name":"SRZ190804","link_type":"DATA_SOURCE","link_url":"https://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?analysis=SRZ190804"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/12f32054-8f18-4dae-8959-bfce7e3108e7"}],"name":"Single-cell sequencing links multiregional immune landscapes and tissue-resident T cells in ccRCC to tumor topology and therapy efficacy","published_at":"2023-07-03T16:11:06+00:00","publisher_metadata":{"authors":[{"family":"Krishna","given":"Chirag"},{"family":"DiNatale","given":"Renzo G."},{"family":"Kuo","given":"Fengshen"},{"family":"Srivastava","given":"Raghvendra M."},{"family":"Vuong","given":"Lynda"},{"family":"Chowell","given":"Diego"},{"family":"Gupta","given":"Sounak"},{"family":"Vanderbilt","given":"Chad"},{"family":"Purohit","given":"Tanaya A."},{"family":"Liu","given":"Ming"},{"family":"Kansler","given":"Emily"},{"family":"Nixon","given":"Briana G."},{"family":"Chen","given":"Ying-Bei"},{"family":"Makarov","given":"Vladimir"},{"family":"Blum","given":"Kyle A."},{"family":"Attalla","given":"Kyrollis"},{"family":"Weng","given":"Stanley"},{"family":"Salmans","given":"Michael L."},{"family":"Golkaram","given":"Mahdi"},{"family":"Liu","given":"Li"},{"family":"Zhang","given":"Shile"},{"family":"Vijayaraghavan","given":"Raakhee"},{"family":"Pawlowski","given":"Traci"},{"family":"Reuter","given":"Victor"},{"family":"Carlo","given":"Maria I."},{"family":"Voss","given":"Martin H."},{"family":"Coleman","given":"Jonathan"},{"family":"Russo","given":"Paul"},{"family":"Motzer","given":"Robert J."},{"family":"Li","given":"Ming O."},{"family":"Leslie","given":"Christina S."},{"family":"Chan","given":"Timothy A."},{"family":"Hakimi","given":"A. Ari"}],"is_preprint":false,"journal":"Cancer Cell","published_at":1619827200.0,"published_day":1,"published_month":5,"published_year":2021},"revised_at":"2026-06-11T16:53:38+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"9416fa0f-fafa-49df-9b23-0234f513dad3","collection_url":"https://cellxgene.cziscience.com/collections/9416fa0f-fafa-49df-9b23-0234f513dad3","collection_version_id":"17dd4524-f44e-4aab-8216-4576f5b86ef4","consortia":[],"contact_email":"wtk22@cam.ac.uk","contact_name":"Walid Khaled","created_at":"2026-06-10T01:50:59+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"12445b6d-4657-47d7-af4f-06f5a6bc6887","dataset_version_id":"b44643bd-7f67-4917-a385-d90e1899b452","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"mammary gland","ontology_term_id":"UBERON:0001911","tissue_type":"tissue"}]}],"description":"Characterising the hierarchy of mammary epithelial cells (MECs) and how they are regulated\nduring adult development is important for understanding how breast cancer arises. Here we\nreport the use of single-cell RNA sequencing to determine the gene expression profile of\nMECs across four developmental stages; nulliparous, mid gestation, lactation and post\ninvolution. Our analysis of 23,184 cells identifies 15 clusters, few of which could be fully\ncharacterised by a single marker gene. We argue instead that the epithelial cells\u2014especially\nin the luminal compartment\u2014should rather be conceptualised as being part of a continuous\nspectrum of differentiation. Furthermore, our data support the existence of a common luminal\nprogenitor cell giving rise to intermediate, restricted alveolar and hormone-sensing pro-\ngenitors. This luminal progenitor compartment undergoes transcriptional changes in\nresponse to a full pregnancy, lactation and involution. In summary, our results provide a\nglobal, unbiased view of adult mammary gland development.","doi":"10.1038/s41467-017-02001-5","is_pre_analysis":false,"links":[{"link_name":"GSE106273","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106273"},{"link_name":"","link_type":"OTHER","link_url":"https://github.com/MarioniLab/MammaryGland"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://marionilab.cruk.cam.ac.uk/mammaryGland"}],"name":"Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing","published_at":"2025-10-16T17:11:54+00:00","publisher_metadata":{"authors":[{"family":"Bach","given":"Karsten"},{"family":"Pensa","given":"Sara"},{"family":"Grzelak","given":"Marta"},{"family":"Hadfield","given":"James"},{"family":"Adams","given":"David J."},{"family":"Marioni","given":"John C."},{"family":"Khaled","given":"Walid T."}],"is_preprint":false,"journal":"Nat Commun","published_at":1512950400.0,"published_day":11,"published_month":12,"published_year":2017},"revised_at":"2026-06-11T16:53:40+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c9706a92-0e5f-46c1-96d8-20e42467f287","collection_url":"https://cellxgene.cziscience.com/collections/c9706a92-0e5f-46c1-96d8-20e42467f287","collection_version_id":"86834318-363f-41bf-b852-0879d386b473","consortia":["CZI Cell Science"],"contact_email":"hnakshat@iupui.edu","contact_name":"Harikrishna Nakshatri","created_at":"2026-06-10T00:50:28+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"de985818-285f-4f59-9dbd-d74968fddba3","dataset_version_id":"8bd3e220-f9dd-4088-ba39-0c72767b5ed9","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"upper outer quadrant of breast","ontology_term_id":"UBERON:0035328","tissue_type":"tissue"}]}],"description":"Single-cell RNA sequencing (scRNA-seq) is an evolving technology used to elucidate the cellular architecture of adult organs. Previous scRNA-seq on breast tissue utilized reduction mammoplasty samples, which are often histologically abnormal. We report a rapid tissue collection/processing protocol to perform scRNA-seq of breast biopsies of healthy women and identify 23 breast epithelial cell clusters. Putative cell-of-origin signatures derived from these clusters are applied to analyze transcriptomes of ~3,000 breast cancers. Gene signatures derived from mature luminal cell clusters are enriched in ~68% of breast cancers, whereas a signature from a luminal progenitor cluster is enriched in ~20% of breast cancers. Overexpression of luminal progenitor cluster-derived signatures in HER2+, but not in other subtypes, is associated with unfavorable outcome. We identify TBX3 and PDK4 as genes co-expressed with estrogen receptor (ER) in the normal breasts, and their expression analyses in >550 breast cancers enable prognostically relevant subclassification of ER+ breast cancers.","doi":"10.1016/j.xcrm.2021.100219","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/a004b150-1c36-4af6-9bbd-070c06dbc17d"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164898"}],"name":"A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells","published_at":"2021-03-25T15:36:05+00:00","publisher_metadata":{"authors":[{"family":"Bhat-Nakshatri","given":"Poornima"},{"family":"Gao","given":"Hongyu"},{"family":"Sheng","given":"Liu"},{"family":"McGuire","given":"Patrick C."},{"family":"Xuei","given":"Xiaoling"},{"family":"Wan","given":"Jun"},{"family":"Liu","given":"Yunlong"},{"family":"Althouse","given":"Sandra K."},{"family":"Colter","given":"Austyn"},{"family":"Sandusky","given":"George"},{"family":"Storniolo","given":"Anna Maria"},{"family":"Nakshatri","given":"Harikrishna"}],"is_preprint":false,"journal":"Cell Reports Medicine","published_at":1614556800.0,"published_day":1,"published_month":3,"published_year":2021},"revised_at":"2026-06-11T16:53:34+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"4828d33d-fb26-42e7-bf36-18293b0eec85","collection_url":"https://cellxgene.cziscience.com/collections/4828d33d-fb26-42e7-bf36-18293b0eec85","collection_version_id":"20ba5b27-3e39-427d-89d5-4a51b0fb0df8","consortia":["CZ Biohub"],"contact_email":"anna.molofsky@ucsf.edu","contact_name":"Anna Molofsky","created_at":"2026-06-10T04:00:52+00:00","curator_name":"Corinn Sophia Small","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"5dec4249-8459-4df0-8998-37193135754c","dataset_version_id":"b85e8f33-1e23-4369-afaa-8bd39edbc667","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"barrel cortex","ontology_term_id":"UBERON:0010415","tissue_type":"tissue"}]}],"description":"Microglia are brain resident phagocytes that can engulf synaptic components and extracellular matrix as well as whole neurons. However, whether there are unique molecular mechanisms that regulate these distinct phagocytic states is unknown. Here we define a molecularly distinct microglial subset whose function is to engulf neurons in the developing brain. We transcriptomically identified a cluster of Type I interferon (IFN-I) responsive microglia that expanded 20-fold in the postnatal day 5 somatosensory cortex after partial whisker deprivation, a stressor that accelerates neural circuit remodeling. In situ, IFN-I responsive microglia were highly phagocytic and actively engulfed whole neurons. Conditional deletion of IFN-I signaling (Ifnar1fl/fl) in microglia but not neurons resulted in dysmorphic microglia with stalled phagocytosis and an accumulation of neurons with double strand DNA breaks, a marker of cell stress. Conversely, exogenous IFN-I was sufficient to drive neuronal engulfment by microglia and restrict the accumulation of damaged neurons. IFN-I deficient mice had excess excitatory neurons in the developing somatosensory cortex as well as tactile hypersensitivity to whisker stimulation. These data define a molecular mechanism through which microglia engulf neurons during a critical window of brain development. More broadly, they reveal key homeostatic roles of a canonical antiviral signaling pathway in brain development.","doi":"10.1016/j.cell.2024.02.020","is_pre_analysis":false,"links":[{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://www.annamolofskylab.org/people"},{"link_name":"GSE173173","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173173"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://lcdorman.shinyapps.io/MouseCortex/"}],"name":"Type I interferon responsive microglia shape cortical development and behavior","published_at":"2024-04-01T16:21:34+00:00","publisher_metadata":{"authors":[{"family":"Escoubas","given":"Caroline C."},{"family":"Dorman","given":"Leah C."},{"family":"Nguyen","given":"Phi T."},{"family":"Lagares-Linares","given":"Christian"},{"family":"Nakajo","given":"Haruna"},{"family":"Anderson","given":"Sarah R."},{"family":"Barron","given":"Jerika J."},{"family":"Wade","given":"Sarah D."},{"family":"Cuevas","given":"Beatriz"},{"family":"Vainchtein","given":"Ilia D."},{"family":"Silva","given":"Nicholas J."},{"family":"Guajardo","given":"Ricardo"},{"family":"Xiao","given":"Yinghong"},{"family":"Lidsky","given":"Peter V."},{"family":"Wang","given":"Ellen Y."},{"family":"Rivera","given":"Brianna M."},{"family":"Taloma","given":"Sunrae E."},{"family":"Kim","given":"Dong Kyu"},{"family":"Kaminskaya","given":"Elizaveta"},{"family":"Nakao-Inoue","given":"Hiromi"},{"family":"Schwer","given":"Bjoern"},{"family":"Arnold","given":"Thomas D."},{"family":"Molofsky","given":"Ari B."},{"family":"Condello","given":"Carlo"},{"family":"Andino","given":"Raul"},{"family":"Nowakowski","given":"Tomasz J."},{"family":"Molofsky","given":"Anna V."}],"is_preprint":false,"journal":"Cell","published_at":1711929600.0,"published_day":1,"published_month":4,"published_year":2024},"revised_at":"2026-06-11T16:53:37+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"d0941303-7ce3-4422-9249-cf31eb98c480","collection_url":"https://cellxgene.cziscience.com/collections/d0941303-7ce3-4422-9249-cf31eb98c480","collection_version_id":"4cd099c6-014b-4032-a30b-a26ae8b74905","consortia":[],"contact_email":"lukas.steuernagel@sf.mpg.de","contact_name":"Lukas Steuernagel","created_at":"2026-06-10T20:24:06+00:00","curator_name":"Brian J Mott","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"a2c833f7-b7f1-4f4d-ad31-cae478b601b7","dataset_version_id":"af06d70d-a2bc-43c1-8378-bc545bc8ee2c","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"hypothalamus","ontology_term_id":"UBERON:0001898","tissue_type":"tissue"}]}],"description":"The hypothalamus is a brain region that plays a key role in coordinating fundamental biological functions. Here, we combine single-nucleus sequencing of 433,369 human hypothalamic cells with spatial transcriptomics, generating a comprehensive spatiocellular transcriptional map of the hypothalamus, the HYPOMAP. The sn-seq data comprises 166,475 neurons, 175,109 oligodendrocytes, 63,111 Astro-Ependymal cells and 28,674 cells from other non-neuronal cell types including microglia and endothelial cells. We adopted a multi-level hierarchical clustering to generate generate a final clustering tree of the data consisting of 5 levels and up to 452 clusters. Spatial transcriptomic data of the human hypothalamus from 9 slices generated with 10x Genomics Visium CytAssist v.2 is available from the Visium CytAssist v.2 link to the right.","doi":"10.1038/s41586-024-08504-8","is_pre_analysis":false,"links":[{"link_name":"","link_type":"RAW_DATA","link_url":"https://data.nemoarchive.org/biccn/grant/u01_lein/linnarsson/transcriptome/sncell/10x_v3/human/raw/"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://ega-archive.org/datasets/EGAD50000000997"},{"link_name":"Visium CytAssist v.2","link_type":"OTHER","link_url":"https://hypomap.sf.mpg.de/view/humanHYPOMAP_ST.h5ad/"}],"name":"HYPOMAP: A comprehensive spatio-cellularmap of the human hypothalamus","published_at":"2025-02-04T00:29:56+00:00","publisher_metadata":{"authors":[{"family":"Tadross","given":"John A."},{"family":"Steuernagel","given":"Lukas"},{"family":"Dowsett","given":"Georgina K. C."},{"family":"Kentistou","given":"Katherine A."},{"family":"Lundh","given":"Sofia"},{"family":"Porniece","given":"Marta"},{"family":"Klemm","given":"Paul"},{"family":"Rainbow","given":"Kara"},{"family":"Hvid","given":"Henning"},{"family":"Kania","given":"Katarzyna"},{"family":"Polex-Wolf","given":"Joseph"},{"family":"Knudsen","given":"Lotte Bjerre"},{"family":"Pyke","given":"Charles"},{"family":"Perry","given":"John R. B."},{"family":"Lam","given":"Brian Y. H."},{"family":"Br\u00fcning","given":"Jens C."},{"family":"Yeo","given":"Giles S. H."}],"is_preprint":false,"journal":"Nature","published_at":1742428800.0,"published_day":20,"published_month":3,"published_year":2025},"revised_at":"2026-06-11T16:55:43+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"ddfad306-714d-4cc0-9985-d9072820c530","collection_url":"https://cellxgene.cziscience.com/collections/ddfad306-714d-4cc0-9985-d9072820c530","collection_version_id":"72dcd7cd-46d6-4d0a-ab7a-691f6b8567d4","consortia":["Wellcome HCA Strategic Science Support"],"contact_email":"m.a.haniffa@newcastle.ac.uk","contact_name":"Muzlifah Haniffa","created_at":"2026-06-10T03:19:18+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' transcription profiling","ontology_term_id":"EFO:0030003"}],"dataset_id":"c7775e88-49bf-4ba2-a03b-93f00447c958","dataset_version_id":"fe2e847c-1602-4f1b-86a4-112e4dc7a8e3","disease":[{"label":"COVID-19","ontology_term_id":"MONDO:0100096"},{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"respiratory system disorder","ontology_term_id":"MONDO:0005087"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"blood","ontology_term_id":"UBERON:0000178","tissue_type":"tissue"}]}],"description":"Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy.","doi":"10.1038/s41591-021-01329-2","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/scCOVID-19/COVIDPBMC/"},{"link_name":"","link_type":"LAB_WEBSITE","link_url":"https://haniffalab.com/"},{"link_name":"E-MTAB-10026","link_type":"DATA_SOURCE","link_url":"https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10026"},{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/b963bd4b-4bc1-4404-8425-69d74bc636b8"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=covid19-pbmc"},{"link_name":"EGAS00001005465","link_type":"RAW_DATA","link_url":"https://ega-archive.org/studies/EGAS00001005465"}],"name":"Single-cell multi-omics analysis of the immune response in COVID-19","published_at":"2021-12-09T22:27:02+00:00","publisher_metadata":{"authors":[{"name":"Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID-19 BioResource Collaboration"},{"family":"Stephenson","given":"Emily"},{"family":"Reynolds","given":"Gary"},{"family":"Botting","given":"Rachel A."},{"family":"Calero-Nieto","given":"Fernando J."},{"family":"Morgan","given":"Michael D."},{"family":"Tuong","given":"Zewen Kelvin"},{"family":"Bach","given":"Karsten"},{"family":"Sungnak","given":"Waradon"},{"family":"Worlock","given":"Kaylee B."},{"family":"Yoshida","given":"Masahiro"},{"family":"Kumasaka","given":"Natsuhiko"},{"family":"Kania","given":"Katarzyna"},{"family":"Engelbert","given":"Justin"},{"family":"Olabi","given":"Bayanne"},{"family":"Spegarova","given":"Jarmila Stremenova"},{"family":"Wilson","given":"Nicola K."},{"family":"Mende","given":"Nicole"},{"family":"Jardine","given":"Laura"},{"family":"Gardner","given":"Louis C. S."},{"family":"Goh","given":"Issac"},{"family":"Horsfall","given":"Dave"},{"family":"McGrath","given":"Jim"},{"family":"Webb","given":"Simone"},{"family":"Mather","given":"Michael W."},{"family":"Lindeboom","given":"Rik G. H."},{"family":"Dann","given":"Emma"},{"family":"Huang","given":"Ni"},{"family":"Polanski","given":"Krzysztof"},{"family":"Prigmore","given":"Elena"},{"family":"Gothe","given":"Florian"},{"family":"Scott","given":"Jonathan"},{"family":"Payne","given":"Rebecca P."},{"family":"Baker","given":"Kenneth F."},{"family":"Hanrath","given":"Aidan T."},{"family":"Schim van der Loeff","given":"Ina C. D."},{"family":"Barr","given":"Andrew S."},{"family":"Sanchez-Gonzalez","given":"Amada"},{"family":"Bergamaschi","given":"Laura"},{"family":"Mescia","given":"Federica"},{"family":"Barnes","given":"Josephine L."},{"family":"Kilich","given":"Eliz"},{"family":"de Wilton","given":"Angus"},{"family":"Saigal","given":"Anita"},{"family":"Saleh","given":"Aarash"},{"family":"Janes","given":"Sam M."},{"family":"Smith","given":"Claire M."},{"family":"Gopee","given":"Nusayhah"},{"family":"Wilson","given":"Caroline"},{"family":"Coupland","given":"Paul"},{"family":"Coxhead","given":"Jonathan M."},{"family":"Kiselev","given":"Vladimir Yu"},{"family":"van Dongen","given":"Stijn"},{"family":"Bacardit","given":"Jaume"},{"family":"King","given":"Hamish W."},{"family":"Rostron","given":"Anthony J."},{"family":"Simpson","given":"A. John"},{"family":"Hambleton","given":"Sophie"},{"family":"Laurenti","given":"Elisa"},{"family":"Lyons","given":"Paul A."},{"family":"Meyer","given":"Kerstin B."},{"family":"Nikoli\u0107","given":"Marko Z."},{"family":"Duncan","given":"Christopher J. A."},{"family":"Smith","given":"Kenneth G. C."},{"family":"Teichmann","given":"Sarah A."},{"family":"Clatworthy","given":"Menna R."},{"family":"Marioni","given":"John C."},{"family":"G\u00f6ttgens","given":"Berthold"},{"family":"Haniffa","given":"Muzlifah"}],"is_preprint":false,"journal":"Nat Med","published_at":1619827200.0,"published_day":1,"published_month":5,"published_year":2021},"revised_at":"2026-06-11T16:53:34+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"33d19f34-87f5-455b-8ca5-9023a2e5453d","collection_url":"https://cellxgene.cziscience.com/collections/33d19f34-87f5-455b-8ca5-9023a2e5453d","collection_version_id":"f3338839-a5d2-47c0-8fa2-c108ad86e87c","consortia":["Gut Cell Atlas"],"contact_email":"fabian.theis@helmholtz-muenchen.de","contact_name":"Fabian Theis","created_at":"2026-06-10T15:13:36+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"}],"dataset_id":"4dd00779-7f73-4f50-89bb-e2d3c6b71b18","dataset_version_id":"774d77e7-210d-4237-8ca8-8d2bb841a2e4","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"caecum epithelium","ontology_term_id":"UBERON:0005636","tissue_type":"tissue"},{"label":"colonic epithelium","ontology_term_id":"UBERON:0000397","tissue_type":"tissue"},{"label":"transverse colon epithelium","ontology_term_id":"UBERON:7770006","tissue_type":"tissue"}]}],"description":"Genome-wide association studies (GWAS) have revealed risk alleles for ulcerative colitis (UC). To understand their cell type specificities and pathways of action, we generate an atlas of 366,650 cells from the colon mucosa of 18 UC patients and 12 healthy individuals, revealing 51 epithelial, stromal, and immune cell subsets, including BEST4+ enterocytes, microfold-like cells, and IL13RA2+IL11+ inflammatory fibroblasts, which we associate with resistance to anti-TNF treatment. Inflammatory fibroblasts, inflammatory monocytes, microfold-like cells, and T cells that co-express CD8 and IL-17 expand with disease, forming intercellular interaction hubs. Many UC risk genes are cell type specific and co-regulated within relatively few gene modules, suggesting convergence onto limited sets of cell types and pathways. Using this observation, we nominate and infer functions for specific risk genes across GWAS loci. Our work provides a framework for interrogating complex human diseases and mapping risk variants to cell types and pathways.","doi":"10.1016/j.cell.2019.06.029","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://explore.data.humancellatlas.org/projects/cd61771b-661a-4e19-b269-6e5d95350de6"},{"link_name":"","link_type":"OTHER","link_url":"https://singlecell.broadinstitute.org/single_cell/study/SCP259"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=human-colon"}],"name":"Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis","published_at":"2023-01-07T00:18:28+00:00","publisher_metadata":{"authors":[{"family":"Smillie","given":"Christopher S."},{"family":"Biton","given":"Moshe"},{"family":"Ordovas-Montanes","given":"Jose"},{"family":"Sullivan","given":"Keri M."},{"family":"Burgin","given":"Grace"},{"family":"Graham","given":"Daniel B."},{"family":"Herbst","given":"Rebecca H."},{"family":"Rogel","given":"Noga"},{"family":"Slyper","given":"Michal"},{"family":"Waldman","given":"Julia"},{"family":"Sud","given":"Malika"},{"family":"Andrews","given":"Elizabeth"},{"family":"Velonias","given":"Gabriella"},{"family":"Haber","given":"Adam L."},{"family":"Jagadeesh","given":"Karthik"},{"family":"Vickovic","given":"Sanja"},{"family":"Yao","given":"Junmei"},{"family":"Stevens","given":"Christine"},{"family":"Dionne","given":"Danielle"},{"family":"Nguyen","given":"Lan T."},{"family":"Villani","given":"Alexandra-Chlo\u00e9"},{"family":"Hofree","given":"Matan"},{"family":"Creasey","given":"Elizabeth A."},{"family":"Huang","given":"Hailiang"},{"family":"Rozenblatt-Rosen","given":"Orit"},{"family":"Garber","given":"John J."},{"family":"Khalili","given":"Hamed"},{"family":"Desch","given":"A. Nicole"},{"family":"Daly","given":"Mark J."},{"family":"Ananthakrishnan","given":"Ashwin N."},{"family":"Shalek","given":"Alex K."},{"family":"Xavier","given":"Ramnik J."},{"family":"Regev","given":"Aviv"}],"is_preprint":false,"journal":"Cell","published_at":1561939200.0,"published_day":1,"published_month":7,"published_year":2019},"revised_at":"2026-06-11T16:53:38+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"c450e15d-321a-42d6-986b-11409d04896d","collection_url":"https://cellxgene.cziscience.com/collections/c450e15d-321a-42d6-986b-11409d04896d","collection_version_id":"48d59f8c-82fc-4e3f-8e58-4eb7d2277a4b","consortia":[],"contact_email":"drhochbaum@gmail.com","contact_name":"Daniel Hochbaum","created_at":"2026-06-10T04:01:34+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"12990215-ad1a-4106-8536-7388327a616f","dataset_version_id":"06477893-027f-462c-9884-5eb893dc741a","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebral cortex","ontology_term_id":"UBERON:0000956","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"1229ecc2-b067-4664-91da-0251aec31574","dataset_version_id":"c025da2e-b6bf-48c2-ba7f-edaba60b7b5d","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"cerebral cortex","ontology_term_id":"UBERON:0000956","tissue_type":"tissue"}]}],"description":"Animals adapt to varying environmental conditions by modifying the function of their internal organs, including the brain. To be adaptive, alterations in behavior must be coordinated with the functional state of organs throughout the body. Here we find that thyroid hormone\u2014 a prominent regulator of metabolism in many peripheral organs\u2014 activates cell-type specific transcriptional programs in anterior regions of cortex of adult male mice via direct activation of thyroid hormone receptors. These programs are enriched for axon-guidance genes in glutamatergic projection neurons, synaptic regulatory genes in both astrocytes and neurons, and pro-myelination factors in oligodendrocytes, suggesting widespread plasticity of cortical circuits. Indeed, whole-cell electrophysiology revealed that thyroid hormone alters excitatory and inhibitory synaptic transmission evoked by activity of cortico-cortical projections, an effect that requires thyroid hormone-induced gene regulatory programs in presynaptic neurons. Furthermore, thyroid hormone activation of transcriptionally mediated circuit plasticity in anterior cortex regulates innate exploratory behaviors and causally promotes exploratory decision-making. Thus, thyroid hormone acts directly on adult cerebral cortex of male mice to coordinate exploratory behaviors with whole-body metabolic state.","doi":"10.1016/j.cell.2024.07.041","is_pre_analysis":false,"links":[{"link_name":"GSE271421","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE271421"}],"name":"Thyroid hormone remodels cortex to coordinate body-wide metabolism and exploration","published_at":"2024-08-21T17:17:37+00:00","publisher_metadata":{"authors":[{"family":"Hochbaum","given":"Daniel R."},{"family":"Hulshof","given":"Lauren"},{"family":"Urke","given":"Amanda"},{"family":"Wang","given":"Wengang"},{"family":"Dubinsky","given":"Alexandra C."},{"family":"Farnsworth","given":"Hannah C."},{"family":"Hakim","given":"Richard"},{"family":"Lin","given":"Sherry"},{"family":"Kleinberg","given":"Giona"},{"family":"Robertson","given":"Keiramarie"},{"family":"Park","given":"Canaria"},{"family":"Solberg","given":"Alyssa"},{"family":"Yang","given":"Yechan"},{"family":"Baynard","given":"Caroline"},{"family":"Nadaf","given":"Naeem M."},{"family":"Beron","given":"Celia C."},{"family":"Girasole","given":"Allison E."},{"family":"Chantranupong","given":"Lynne"},{"family":"Cortopassi","given":"Marissa D."},{"family":"Prouty","given":"Shannon"},{"family":"Geistlinger","given":"Ludwig"},{"family":"Banks","given":"Alexander S."},{"family":"Scanlan","given":"Thomas S."},{"family":"Datta","given":"Sandeep Robert"},{"family":"Greenberg","given":"Michael E."},{"family":"Boulting","given":"Gabriella L."},{"family":"Macosko","given":"Evan Z."},{"family":"Sabatini","given":"Bernardo L."}],"is_preprint":false,"journal":"Cell","published_at":1727740800.0,"published_day":1,"published_month":10,"published_year":2024},"revised_at":"2026-06-11T16:53:40+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"3c34e6f1-6827-47dd-8e19-9edcd461893f","collection_url":"https://cellxgene.cziscience.com/collections/3c34e6f1-6827-47dd-8e19-9edcd461893f","collection_version_id":"eca8a4e5-fcd0-4112-bac9-98ade0f314ed","consortia":["Human Cell Atlas (HCA)"],"contact_email":"g.thomas@soton.ac.uk","contact_name":"Gareth Thomas","created_at":"2026-06-10T21:09:18+00:00","curator_name":"Jennifer Yu-Sheng Chien","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"b6b5ea88-e092-46e4-b9c5-e93b52d5c195","dataset_version_id":"9d06247c-6bc3-46b6-be70-5da7ba205957","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"},{"label":"oropharynx squamous cell carcinoma","ontology_term_id":"MONDO:0044704"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"oropharynx","ontology_term_id":"UBERON:0001729","tissue_type":"tissue"}]}],"description":"Single cell RNA sequencing was performed on treatment-na\u00efve tumors and matched-normal mucosa from ten patients with oropharyngeal squamous cell carcinoma. The disaggregation protocol was optimised to broadly capture both immune and non-immune stromal cell populations (particularly cancer-associated fibroblasts). The samples investigated included 7 HPV+ tumors (31,386 cells), 3 HPV- tumors (19,814 cells) and 7 matched-normal mucosa (31,644 cells). Our dataset contains a thorough representation of tumor and stromal cell subpopulations and provides a detailed mapping of \u2018immune hot\u2019 (HPV-positive) and \u2018immune-cold\u2019 (HPV-negative) tumor microenvironments.","doi":"10.1186/s12943-024-02191-9","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://zenodo.org/records/14284357"}],"name":"Characterisation of human papillomavirus (HPV)-positive (immune hot) and HPV-negative (immune cold) head and neck tumors by single cell RNA sequencing","published_at":"2024-12-05T18:32:44+00:00","publisher_metadata":{"authors":[{"family":"Jenkins","given":"Benjamin H."},{"family":"Tracy","given":"Ian"},{"family":"Rodrigues","given":"Maria Fernanda S. D."},{"family":"Smith","given":"Melanie J. 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While several sets of mouse retinal scRNA-seq data have been published, each dataset either has a relatively small number of cells or is limited to a subset of cell types, making each dataset incomplete and suboptimal for the vision community to use. To establish a unified and comprehensive reference for the mouse retina, we first generated the most comprehensive dataset comprising approximately 190,000 single cells from the C57BL/6J mouse retina. This dataset was generated through the targeted enrichment of rare population cells via the application of CD73- and CD90.1+ antibody treatments. By integrating this new dataset with public datasets, we conducted an integrated analysis to construct the Mouse Retina Cell Atlas (MRCA) for wild-type mice, which encompasses over 323,000 single cells. The MRCA characterizes 11 major classes and 137 cell types. It captured consensus cell type characterization from public datasets and identified additional new cell types, such as new cell types for two retinal ganglion cell types, 16_ooDS_DV and 18_Novel. Cross-comparison with functional annotation enabled the novel naming of RGC types. To facilitate the public use of the MRCA, we have deposited it on CELLxGENE, UCSC Cell Browser, and Single Cell Portal for visualization and gene expression exploration. The comprehensive MRCA serves as an easy-to-use, one-stop data resource for the mouse retina communities.","doi":"10.1016/j.isci.2024.109916","is_pre_analysis":false,"links":[{"link_name":"GSE243413","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE243413"}],"name":"Unified comprehensive single-cell atlas of the mouse retina","published_at":"2023-12-15T21:43:25+00:00","publisher_metadata":{"authors":[{"family":"Li","given":"Jin"},{"family":"Choi","given":"Jongsu"},{"family":"Cheng","given":"Xuesen"},{"family":"Ma","given":"Justin"},{"family":"Pema","given":"Shahil"},{"family":"Sanes","given":"Joshua R."},{"family":"Mardon","given":"Graeme"},{"family":"Frankfort","given":"Benjamin J."},{"family":"Tran","given":"Nicholas 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v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"2dc198e1-e0a6-4e88-b7a3-4b66be7e4a4a","dataset_version_id":"19d50d93-ffdd-4122-bfbd-25e0c6dd6531","disease":[{"label":"cystic fibrosis","ontology_term_id":"MONDO:0009061"},{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["cell"],"tissue":[{"label":"lung","ontology_term_id":"UBERON:0002048","tissue_type":"tissue"}]}],"description":"A single cell RNA sequencing atlas of bronchoalveolar lavage (BAL) cells collected from preschool-aged children with cystic fibrosis and non-CF controls.","doi":"10.1016/j.mucimm.2026.03.012","is_pre_analysis":false,"links":[{"link_name":"","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/processing-of-pediatric-bronchoalveolar-lavage-sam-6qpvr8ox2lmk/v1"}],"name":"Single cell RNA sequencing of pediatric bronchoalveolar lavage","published_at":"2026-03-30T21:52:43+00:00","publisher_metadata":{"authors":[{"family":"Maksimovic","given":"Jovana"},{"family":"Shanthikumar","given":"Shivanthan"},{"family":"Howitt","given":"George"},{"family":"Dixit","given":"Gunjan"},{"family":"Hickey","given":"Peter F"},{"family":"Anttila","given":"Casey"},{"family":"Brown","given":"Daniel V."},{"family":"Gubbels","given":"Liam"},{"family":"Senabouth","given":"Anne"},{"family":"Amann-Zalcenstein","given":"Daniela"},{"family":"Powell","given":"Joseph E."},{"family":"Ranganathan","given":"Sarath C."},{"family":"Oshlack","given":"Alicia"},{"family":"Neeland","given":"Melanie R."}],"is_preprint":false,"journal":"Mucosal Immunology","published_at":1780272000.0,"published_day":1,"published_month":6,"published_year":2026},"revised_at":"2026-06-11T16:55:53+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"92fde064-2fb4-41f8-b85c-c6904000b859","collection_url":"https://cellxgene.cziscience.com/collections/92fde064-2fb4-41f8-b85c-c6904000b859","collection_version_id":"fce3663b-bb1a-4601-bbab-0040bfd28a7e","consortia":["European Union\u2019s Horizon 2020"],"contact_email":"c.novella_rausell@lumc.nl","contact_name":"Claudio Novella-Rausell","created_at":"2026-06-10T22:26:27+00:00","curator_name":"Jason Hilton","datasets":[{"assay":[{"label":"10x 3' transcription profiling","ontology_term_id":"EFO:0030003"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"},{"label":"DroNc-seq","ontology_term_id":"EFO:0008720"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"}],"dataset_id":"42bb7f78-cef8-4b0d-9bba-50037d64d8c1","dataset_version_id":"c37ceed4-eb32-4158-8738-fac5f75815cb","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"cortex of kidney","ontology_term_id":"UBERON:0001225","tissue_type":"tissue"},{"label":"inner medulla of kidney","ontology_term_id":"UBERON:0001294","tissue_type":"tissue"},{"label":"kidney","ontology_term_id":"UBERON:0002113","tissue_type":"tissue"},{"label":"outer medulla of kidney","ontology_term_id":"UBERON:0001293","tissue_type":"tissue"},{"label":"renal glomerulus","ontology_term_id":"UBERON:0000074","tissue_type":"tissue"},{"label":"renal medulla","ontology_term_id":"UBERON:0000362","tissue_type":"tissue"}]}],"description":"The cellular diversity and complexity of the kidney are on par with its physiological intricacy. Although our anatomical understanding of the different segments and their functions is supported by a plethora of research, the identification of distinct and rare cell populations and their markers remains elusive. Here, we leverage the large number of cells and nuclei profiles using single-cell (scRNA-seq) and single-nuclei (snRNA-seq) RNA-sequencing to build a comprehensive atlas of the adult mouse kidney. We created MKA (Mouse Kidney Atlas) by integrating 59 publicly available single-cell and single-nuclei transcriptomic datasets from eight independent studies. The atlas contains more than 140.000 cells and nuclei covering different single-cell technologies, age, and tissue sections. To harmonize annotations across datasets, we constructed a hierarchical model of the cell populations present in our atlas. Using this hierarchy, we trained a model to automatically identify cells in unannotated datasets and evaluated its performance against well-established methods and annotation references. Our learnt model is dynamic, allowing the incorporation of novel cell populations and refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies and characterized well-studied and rare cell populations. This allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states.","doi":"10.1016/j.isci.2023.106877","is_pre_analysis":false,"links":[],"name":"A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery","published_at":"2022-07-01T18:52:41+00:00","publisher_metadata":{"authors":[{"family":"Novella-Rausell","given":"Claudio"},{"family":"Grudniewska","given":"Magda"},{"family":"Peters","given":"Dorien J.M."},{"family":"Mahfouz","given":"Ahmed"}],"is_preprint":false,"journal":"iScience","published_at":1685577600.0,"published_day":1,"published_month":6,"published_year":2023},"revised_at":"2026-06-11T16:55:53+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"554fe96e-832b-4651-ac1b-a2df9a6735c3","collection_url":"https://cellxgene.cziscience.com/collections/554fe96e-832b-4651-ac1b-a2df9a6735c3","collection_version_id":"6842e32f-6d09-4949-9631-43a0810be245","consortia":[],"contact_email":"ariel.levine@nih.gov","contact_name":"Ariel Levine","created_at":"2026-06-10T22:50:15+00:00","curator_name":"James Chaffer","datasets":[{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"},{"label":"Fluidigm C1-based SMARTer library preparation","ontology_term_id":"EFO:0010058"},{"label":"SCRB-seq","ontology_term_id":"EFO:0010004"},{"label":"SPLiT-seq","ontology_term_id":"EFO:0009919"}],"dataset_id":"1fd5987c-c4c3-4138-900a-5aea2b59a6f7","dataset_version_id":"03b71780-8180-4bf0-b00e-ec40a1743b9e","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"dorsal horn of spinal cord","ontology_term_id":"UBERON:0002256","tissue_type":"tissue"},{"label":"lumbar spinal cord","ontology_term_id":"UBERON:0002792","tissue_type":"tissue"},{"label":"spinal cord","ontology_term_id":"UBERON:0002240","tissue_type":"tissue"},{"label":"spinocerebellar tract","ontology_term_id":"UBERON:0005413","tissue_type":"tissue"}]},{"assay":[{"label":"10x 3' v1","ontology_term_id":"EFO:0009901"},{"label":"10x 3' v2","ontology_term_id":"EFO:0009899"},{"label":"Drop-seq","ontology_term_id":"EFO:0008722"},{"label":"Fluidigm C1-based SMARTer library preparation","ontology_term_id":"EFO:0010058"},{"label":"SCRB-seq","ontology_term_id":"EFO:0010004"},{"label":"SPLiT-seq","ontology_term_id":"EFO:0009919"}],"dataset_id":"179b00d1-14f5-48ca-8bd6-3a9c7b9e9737","dataset_version_id":"a06bbf90-6a76-4300-984e-6a7d613dab10","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Mus musculus","ontology_term_id":"NCBITaxon:10090"}],"perturbation_types":null,"suspension_type":["nucleus","cell"],"tissue":[{"label":"dorsal horn of spinal cord","ontology_term_id":"UBERON:0002256","tissue_type":"tissue"},{"label":"lumbar spinal cord","ontology_term_id":"UBERON:0002792","tissue_type":"tissue"},{"label":"spinal cord","ontology_term_id":"UBERON:0002240","tissue_type":"tissue"},{"label":"spinocerebellar tract","ontology_term_id":"UBERON:0005413","tissue_type":"tissue"}]}],"description":"Single-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types.","doi":"10.1038/s41467-021-25125-1","is_pre_analysis":false,"links":[],"name":"A harmonized atlas of mouse spinal cord cell types and their spatial organization.","published_at":"2026-01-06T20:38:47+00:00","publisher_metadata":{"authors":[{"family":"Russ","given":"Daniel E."},{"family":"Cross","given":"Ryan B. Patterson"},{"family":"Li","given":"Li"},{"family":"Koch","given":"Stephanie C."},{"family":"Matson","given":"Kaya J. E."},{"family":"Yadav","given":"Archana"},{"family":"Alkaslasi","given":"Mor R."},{"family":"Lee","given":"Dylan I."},{"family":"Le Pichon","given":"Claire E."},{"family":"Menon","given":"Vilas"},{"family":"Levine","given":"Ariel J."}],"is_preprint":false,"journal":"Nat Commun","published_at":1632873600.0,"published_day":29,"published_month":9,"published_year":2021},"revised_at":"2026-06-11T16:55:54+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"7b9ae565-a781-433d-98d4-430394e7802a","collection_url":"https://cellxgene.cziscience.com/collections/7b9ae565-a781-433d-98d4-430394e7802a","collection_version_id":"88cf70b3-d4a2-4a04-a2eb-c800da3328c1","consortia":["CZI Cell Science"],"contact_email":"sarah.snelling@ndorms.ox.ac.uk","contact_name":"Sarah Snelling","created_at":"2026-06-10T22:52:25+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"f641d68a-e877-4bb8-afd7-b8fa3921d461","dataset_version_id":"3c78889f-cedf-4dc7-9a94-a496e8443355","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"calcaneal tendon","ontology_term_id":"UBERON:0003701","tissue_type":"tissue"},{"label":"tendon of quadriceps femoris","ontology_term_id":"UBERON:0014848","tissue_type":"tissue"}]}],"description":"We present a single-nucleus transcriptomic atlas of human foetal tendon development. Using single-nucleus RNA sequencing (snRNA-seq) on Achilles (N = 8) and quadriceps (N = 7) tendons from nine donors aged 12, 17, and 20 post-conception weeks (pcw), we define the cellular composition of the developing tendon. We identify multiple spatially distinct fibroblast subtypes, along with immune, vascular, lymphatic, neural, and muscle cells that collectively shape tendon morphogenesis.","doi":"10.1016/j.celrep.2026.117085","is_pre_analysis":false,"links":[{"link_name":"Github code","link_type":"OTHER","link_url":"https://github.com/AlinaKurjan/DPhilCode"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/032880e5-2b44-4bfb-8eef-25bb48e7453f"}],"name":"Single nucleus transcriptomic atlas of human foetal tendon","published_at":"2025-07-08T18:10:52+00:00","publisher_metadata":{"authors":[{"family":"Kurjan","given":"Alina"},{"family":"Mimpen","given":"Jolet Y."},{"family":"Ramos-Mucci","given":"Lorenzo"},{"family":"Aksu","given":"Ali C."},{"family":"Cohen","given":"Carla J."},{"family":"Naszai","given":"Mate"},{"family":"Buckley","given":"Christopher D."},{"family":"Cribbs","given":"Adam P."},{"family":"Baldwin","given":"Mathew J."},{"family":"Snelling","given":"Sarah J.B."}],"is_preprint":false,"journal":"Cell Reports","published_at":1775001600.0,"published_day":1,"published_month":4,"published_year":2026},"revised_at":"2026-06-11T16:55:55+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"a7e81820-297d-4086-8123-cc7dde64e495","collection_url":"https://cellxgene.cziscience.com/collections/a7e81820-297d-4086-8123-cc7dde64e495","collection_version_id":"15abfc18-5673-42ad-b70f-e04dc59971d9","consortia":["CZI Cell Science"],"contact_email":"sarah.snelling@ndorms.ox.ac.uk","contact_name":"Sarah Snelling","created_at":"2026-06-10T23:22:34+00:00","curator_name":"Jennifer Zamanian","datasets":[{"assay":[{"label":"10x 3' v3","ontology_term_id":"EFO:0009922"}],"dataset_id":"ef0fc6ac-4872-40e1-ab24-e445b19ca6e3","dataset_version_id":"accd7d2e-d67d-4b91-9ea1-f2d1eee78ebf","disease":[{"label":"normal","ontology_term_id":"PATO:0000461"}],"genetic_perturbation_strategy":null,"is_pre_analysis":false,"organism":[{"label":"Homo sapiens","ontology_term_id":"NCBITaxon:9606"}],"perturbation_types":null,"suspension_type":["nucleus"],"tissue":[{"label":"calcaneal tendon","ontology_term_id":"UBERON:0003701","tissue_type":"tissue"}]}],"description":"Tendons are transitional tissues linking muscle to bone, enabling locomotion and fine motor control. The cellular biology across the Achilles tendon unit is poorly understood, yet critical for interpreting normal function and pathological changes across its microanatomically-defined functional zones. We generated a spatially-resolved transcriptomic atlas of human Achilles tendon, sampling the tendon-bone junction (enthesis), midbody, myotendinous junction, and adjoining muscle. Six fibroblast subtypes were identified, with distinct transcriptional profiles and spatial distributions, suggesting specialised functional roles across the tendon-muscle unit. Two dominant fibroblast types were specifically positioned in the tendon mid-substance, and paratenon (vessel-rich region surrounding the tendon fibrils); other populations included perineural, myotendinous junction-specific, muscle-specific, and lining-layer fibroblasts. These findings demonstrate how cellular diversity across a transitional tissue may underlie microanatomical-specific roles. This atlas provides a foundation for understanding cellular functions across the tendon-muscle unit and will be essential for comparisons with diseased tissue, identifying pathogenic mediators and treatment targets for autoimmune and degenerative pathologies of the Achilles tendon.","doi":"10.1152/ajpcell.00838.2025","is_pre_analysis":false,"links":[],"name":"Fibroblast specialisation across microanatomy in a single-cell atlas of healthy human Achilles tendon","published_at":"2026-04-13T17:03:48+00:00","publisher_metadata":{"authors":[{"family":"Cohen","given":"Carla J."},{"family":"Mimpen","given":"Jolet Y."},{"family":"Kurjan","given":"Alina"},{"family":"Paul","given":"Claudia"},{"family":"Sharma","given":"Shreeya"},{"family":"Ramos-Mucci","given":"Lorenzo"},{"family":"Ikwuanusi","given":"Chinemerem T."},{"family":"Aksu","given":"Ali Cenk"},{"family":"Boakye Serebour","given":"Tracy"},{"family":"Nikolic","given":"Marina"},{"family":"Rue-Albrecht","given":"Kevin"},{"family":"Gibbons","given":"Christopher"},{"family":"Whitwell","given":"Duncan"},{"family":"Cosker","given":"Tom"},{"family":"Gwilym","given":"Steven"},{"family":"Siddiqi","given":"Ather"},{"family":"Rajasekaran","given":"Raja Bhaskara"},{"family":"Branford-White","given":"Harriet"},{"family":"Cribbs","given":"Adam P."},{"family":"Hulley","given":"Philippa A."},{"family":"Sims","given":"David"},{"family":"Baldwin","given":"Mathew J."},{"family":"Snelling","given":"Sarah J. B."}],"is_preprint":false,"journal":"American Journal of Physiology-Cell Physiology","published_at":1777593600.0,"published_day":1,"published_month":5,"published_year":2026},"revised_at":"2026-06-11T16:55:56+00:00","revising_in":null,"revision_of":null,"visibility":"PUBLIC"},{"collection_id":"fc19ae6c-d7c1-4dce-b703-62c5d52061b4","collection_url":"https://cellxgene.cziscience.com/collections/fc19ae6c-d7c1-4dce-b703-62c5d52061b4","collection_version_id":"e34bf438-57d4-4e24-a8cc-5f7ff9cc672b","consortia":["CZI Cell Science"],"contact_email":"st9@sanger.ac.uk","contact_name":"Sarah A. 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In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the microanatomical underpinnings of this process in pre- and early postnatal stages, we established a quantitative morphological framework for the thymus\u2014the Cortico-Medullary Axis\u2014and used it to perform a spatially resolved analysis. By applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions by the beginning of the second trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall\u2019s corpuscles and identify divergence in the timing of medullary entry between CD4 and CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation and Organ Axis construction (TissueTag), which can be applied to any tissue.","doi":"10.1038/s41586-024-07944-6","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://github.com/Teichlab/thymus_spatial_atlas/tree/main"},{"link_name":"BioImage 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Homeostatic interactions between injured kidney epithelium and its surrounding milieu determine successful repair outcomes, while pathogenic signaling promotes unresolved inflammation and fibrosis leading to chronic disease. We integrated multiple single-cell and spatial modalities across ~700 samples from >350 patients (~250 research biopsies), analyzing ~1.7 million cells alongside complementary mouse multi-omic profiles spanning acute-to-chronic injury and aging (>300,000 cells) and spatial transcriptomic analysis of 150 human biopsies. This cross-species atlas delineates functional pathways and druggable targets across the nephron and defines gene regulatory networks and chromatin landscapes governing tubular, fibroblast, and immune cell transitions from injury to either recovery or failed repair states. We identified distinct cellular states associated with specific pathological features that show dynamic distributions between acute kidney injury (AKI) and chronic kidney disease (CKD), organized within unique spatial niches that reveal progression mechanisms from early injury to unresolved disease. Gene regulatory analyses prioritized key transcription factor activities (SOX4, SOX9, NFKB1, REL, KLFs) and their target networks establishing disease states and tissue microenvironments. These regulatory programs were directly linked to clinical outcomes, identifying molecular signatures of recovery and secreted biomarkers predictive of AKI-to-CKD progression, providing a key resource for therapeutic development and precision medicine approaches in kidney disease.","doi":"10.1101/2025.09.26.678707","is_pre_analysis":false,"links":[{"link_name":"Single-Nucleus RNA-sequencing","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/10x-genomics-single-nucleus-rna-sequencing-for-tra-e6nvw99wzgmk/v3"},{"link_name":"Isolation of single nuclei from solid tissues","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/isolation-of-single-nuclei-from-solid-tissues-5qpvonb6bl4o/v1"},{"link_name":"Single cell RNA sequencing (scRNA-seq)","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/single-cell-rna-sequencing-scrna-seq-eq2ly3zjpgx9/v1"},{"link_name":"10X Genomics Single-nucleus Multiome (RNA+ATAC)","link_type":"PROTOCOL","link_url":"https://www.protocols.io/view/10x-genomics-single-nucleus-multiome-rna-atac-assa-5qpvoby69l4o/v2"},{"link_name":"","link_type":"DATA_SOURCE","link_url":"https://www.kpmp.org/doi-collection/10-48698-16dd-vj20"},{"link_name":"Atlas v2 GitHub","link_type":"OTHER","link_url":"https://github.com/KPMP-Scientific/KPMP-Atlas-v2"}],"name":"Cellular and Spatial Drivers of Unresolved Injury and Functional Decline in the Human Kidney","published_at":"2025-11-12T17:14:14+00:00","publisher_metadata":{"authors":[{"family":"Lake","given":"Blue B."},{"family":"Melo Ferreira","given":"Ricardo"},{"family":"Hansen","given":"Jens"},{"family":"Menon","given":"Rajasree"},{"family":"Basta","given":"Jeannine"},{"family":"Thiessen Philbrook","given":"Heather"},{"family":"Reinert","given":"Stephanie"},{"family":"Fallegger","given":"Robin"},{"family":"Lagwankar","given":"Asmita K."},{"family":"Chen","given":"Xi"},{"family":"Maity","given":"Soumya"},{"family":"Djambazova","given":"Katerina V."},{"family":"Gorman","given":"Brittney L."},{"family":"Lucarelli","given":"Nicholas"},{"family":"Gisch","given":"Debora L."},{"family":"Schmidt","given":"Insa M."},{"family":"Nair","given":"Viji"},{"family":"Alakwaa","given":"Fadhl"},{"family":"Kefaloyianni","given":"Eirini"},{"family":"Zhang","given":"Bo"},{"family":"Knoten","given":"Amanda L."},{"family":"Kaushal","given":"Madhurima"},{"family":"Otto","given":"Edgar A."},{"family":"Farrow","given":"Melissa A."},{"family":"Diep","given":"Dinh"},{"family":"Velickovic","given":"Dusan"},{"family":"Sabo","given":"Angela R."},{"family":"Cole","given":"Elijah"},{"family":"Tamayo","given":"Ian"},{"family":"Tanevski","given":"Jovan"},{"family":"Conklin","given":"Kimberly Y."},{"family":"Sealfon","given":"Rachel S. 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Here, we analyzed the phenotype, transcriptome, function, and repertoire of human \u03b3\u03b4 T cells in blood, mucosal and lymphoid tissues from 176 donors across the lifespan, revealing distinct profiles in children compared to adults. In early life, clonally diverse V\u03b41 subsets predominate across blood and tissues, comprising na\u00efve and differentiated effector and tissue repair functions, while cytolytic V\u03b42 subsets populate blood, spleen and lungs. Over age, both subsets exhibit clonal expansions disseminated across sites and express elevated cytolytic signatures. In adults, V\u03b42 cells predominate in blood, while V\u03b41 cells are enriched across tissues and express residency profiles. These results indicate that antigenic exposures over childhood drive the functional evolution and tissue compartmentalization of \u03b3\u03b4 T cells, leading to age-dependent roles in immunity.","doi":"10.1126/sciimmunol.adn3954","is_pre_analysis":false,"links":[{"link_name":"GSE240858","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE240858"}],"name":"Human \u03b3\u03b4 T cells in diverse tissues exhibit site-specific maturation dynamics across the lifespan","published_at":"2024-09-10T22:48:46+00:00","publisher_metadata":{"authors":[{"family":"Gray","given":"Joshua I."},{"family":"Caron","given":"Daniel P."},{"family":"Wells","given":"Steven B."},{"family":"Guyer","given":"Rebecca"},{"family":"Szabo","given":"Peter"},{"family":"Rainbow","given":"Daniel"},{"family":"Ergen","given":"Can"},{"family":"Rybkina","given":"Ksenia"},{"family":"Bradley","given":"Marissa C."},{"family":"Matsumoto","given":"Rei"},{"family":"Pethe","given":"Kalpana"},{"family":"Kubota","given":"Masaru"},{"family":"Teichmann","given":"Sarah"},{"family":"Jones","given":"Joanne"},{"family":"Yosef","given":"Nir"},{"family":"Atkinson","given":"Mark"},{"family":"Brusko","given":"Maigan"},{"family":"Brusko","given":"Todd M."},{"family":"Connors","given":"Thomas J."},{"family":"Sims","given":"Peter A."},{"family":"Farber","given":"Donna L."}],"is_preprint":false,"journal":"Sci. 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Although major cell types have been identified in the mouse intestinal epithelium, cell type\u2013specific markers and functional assignments are largely unavailable for human intestine. Here, our single-cell RNA-seq analyses of 14,537 epithelial cells from human ileum, colon, and rectum reveal different nutrient absorption preferences in the small and large intestine, suggest the existence of Paneth-like cells in the large intestine, and identify potential new marker genes for human transient-amplifying cells and goblet cells. We have validated some of these insights by quantitative PCR, immunofluorescence, and functional analyses. Furthermore, we show both common and differential features of the cellular landscapes between the human and mouse ilea. Therefore, our data provide the basis for detailed characterization of human intestine cell constitution and functions, which would be helpful for a better understanding of human intestine disorders, such as inflammatory bowel disease and intestinal tumorigenesis.","doi":"10.1084/jem.20191130","is_pre_analysis":false,"links":[{"link_name":"","link_type":"OTHER","link_url":"https://www.ebi.ac.uk/gxa/sc/experiments/E-GEOD-125970"},{"link_name":"","link_type":"OTHER","link_url":"https://cells.ucsc.edu/?ds=human-intestine"},{"link_name":"GSE125970","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE125970"}],"name":"Single-cell transcriptome analysis reveals differential nutrient absorption functions in human 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This comprehensive cell atlas of the healthy adult human intestinal epithelium resolves likely functional differences across anatomical regions along the gastrointestinal tract and advances our understanding of human intestinal physiology.","doi":"10.1016/j.jcmgh.2022.02.007","is_pre_analysis":false,"links":[{"link_name":"GSE185224","link_type":"RAW_DATA","link_url":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185224"},{"link_name":"","link_type":"RAW_DATA","link_url":"https://explore.data.humancellatlas.org/projects/73769e0a-5fcd-41f4-9083-41ae08bfa4c1"}],"name":"A proximal-to-distal survey of healthy adult human small intestine and colon epithelium by single-cell transcriptomics","published_at":"2023-01-05T16:24:52+00:00","publisher_metadata":{"authors":[{"family":"Burclaff","given":"Joseph"},{"family":"Bliton","given":"R. 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We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. 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Here, we generate an in-depth single-cell map of the developing human intestine at 6\u201310 weeks post-conception. Our analysis reveals the transcriptional profile of cycling epithelial precursor cells; distinct from LGR5-expressing cells. We propose that these cells may contribute to differentiated cell subsets via the generation of LGR5-expressing stem cells and receive signals from surrounding mesenchymal cells. Furthermore, we draw parallels between the transcriptomes of ex vivo tissues and in vitro fetal organoids, revealing the maturation of organoid cultures in a dish. Lastly, we compare scRNA-seq profiles from pediatric Crohn\u2019s disease epithelium alongside matched healthy controls to reveal disease-associated changes in the epithelial composition. Contrasting these with the fetal profiles reveals the re-activation of fetal transcription factors in Crohn\u2019s disease. 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These processes rely on the precisely coordinated intricate multicellular interactions across time and space. How aging disrupts these interactions, leading to an overall decline in reproductive and endocrine functions, remains understudied. To understand the multicellular dynamics that underlie ovarian function and their changes with age, here we use Slide-seq, a near-cellular spatial transcriptomics method, to profile 22 mouse ovaries across the reproductive cycle and chronological age, representing 610,620 near-cellular spots across 69 spatial transcriptomic profiles. We develop a segmentation analysis to identify spatial niches that capture different states of folliculogenesis from static snapshots in situ, allowing us to examine the multicellular dynamics of 358 oocytes, 668 follicles, and 236 corpora lutea. We find that aging disrupts both the spatial organization and temporal coordination of folliculogenesis before the cessation of cycling, which may contribute to the dysregulation of hormone production and signaling. These disruptions are marked by altered immune cell dynamics, inflammatory signaling, and global tissue disorganization that impair the cyclic remodeling required for ovarian function. Our findings reveal how multicellular niches orchestrate ovarian function and demonstrate how age-related breakdown of tissue organization across time and space precedes reproductive decline.","doi":"10.1038/s43587-026-01140-z","is_pre_analysis":false,"links":[],"name":"Aging disrupts spatiotemporal coordination in the cycling murine ovary","published_at":"2026-06-22T18:37:18+00:00","publisher_metadata":{"authors":[{"family":"Lan","given":"Tammy C. 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Here, we simultaneously assess microbiota and single immune cells across the healthy, adult human colon, with paired characterization of immune cells in the mesenteric lymph nodes, to delineate colonic immune niches at steady state. We describe distinct helper T cell activation and migration profiles along the colon and characterize the transcriptional adaptation trajectory of regulatory T cells between lymphoid tissue and colon. 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